{"id":32245,"date":"2022-02-04T23:01:57","date_gmt":"2022-02-04T15:01:57","guid":{"rendered":"https:\/\/swarma.org\/?p=32245"},"modified":"2022-02-04T23:01:57","modified_gmt":"2022-02-04T15:01:57","slug":"%e5%89%8d%e6%b2%bf%e7%bb%bc%e8%bf%b0%ef%bc%9a%e9%9b%86%e4%bd%93%e6%99%ba%e8%83%bd%e4%b8%8e%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%e7%9a%84%e4%ba%a4%e5%8f%89%e8%bf%9b%e5%b1%95","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=32245","title":{"rendered":"\u524d\u6cbf\u7efc\u8ff0\uff1a\u96c6\u4f53\u667a\u80fd\u4e0e\u6df1\u5ea6\u5b66\u4e60\u7684\u4ea4\u53c9\u8fdb\u5c55"},"content":{"rendered":"
\n
\n
\n
\n
\n

<\/p>\n<\/section>\n

\n
\n
\n
\n
\n
\n

<\/section>\n<\/section>\n
\n
\n

\u5bfc\u8bed<\/strong><\/p>\n<\/section>\n<\/section>\n

\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
\n
\n
\n

<\/strong>\u5f53\u524d\u6700\u5148\u8fdb\u7684\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u5b58\u5728\u4e00\u4e9b\u6839\u672c\u95ee\u9898\uff0c\u800c\u6765\u81ea\u96c6\u4f53\u667a\u80fd\uff0c\u7279\u522b\u662f\u590d\u6742\u7cfb\u7edf\u7684\u6982\u5ff5\uff0c\u5f80\u5f80\u53ef\u4ee5\u63d0\u4f9b\u6709\u6548\u89e3\u51b3\u65b9\u6848\u3002\u4e8b\u5b9e\u4e0a\uff0c\u590d\u6742\u7cfb\u7edf\u9886\u57df\u7684\u6982\u5ff5\uff0c\u5982\u5143\u80de\u81ea\u52a8\u673a\u3001\u81ea\u7ec4\u7ec7\u3001\u6d8c\u73b0\u3001\u96c6\u4f53\u884c\u4e3a\uff0c\u4e0e\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u6709\u7740\u60a0\u4e45\u7684\u8054\u7cfb\u30022021\u5e7412\u6708arxiv\u4e0a\u520a\u8f7d\u7684\u4e00\u7bc7\u7efc\u8ff0\u6587\u7ae0\uff0c\u68b3\u7406\u4e86\u590d\u6742\u7cfb\u7edf\u4e0e\u795e\u7ecf\u7f51\u7edc\u76f8\u4e92\u4ea4\u7ec7\u7684\u53d1\u5c55\u5386\u7a0b\uff0c\u4ece\u56fe\u50cf\u5904\u7406\u3001\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u3001\u591a\u667a\u80fd\u4f53\u5b66\u4e60\u3001\u5143\u5b66\u4e60\u7b49\u51e0\u4e2a\u6d3b\u8dc3\u9886\u57df\uff0c\u5c55\u793a\u4e86\u7ed3\u5408\u96c6\u4f53\u667a\u80fd\u539f\u7406\u5bf9\u6df1\u5ea6\u5b66\u4e60\u7814\u7a76\u7684\u63a8\u52a8\u4f5c\u7528\u3002<\/span><\/strong><\/p>\n


<\/p>\n

\u7814\u7a76\u9886\u57df\uff1a\u6df1\u5ea6\u5b66\u4e60\uff0c\u96c6\u4f53\u667a\u80fd\uff0c\u590d\u6742\u7cfb\u7edf\uff0c\u5143\u80de\u81ea\u52a8\u673a\uff0c\u81ea\u7ec4\u7ec7\uff0c\u6d8c\u73b0<\/strong><\/strong><\/span><\/strong><\/span><\/strong><\/span><\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

\n
\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
\n
<\/strong><\/section>\n<\/section>\n
\n

David Ha, Yujin Tang<\/span> <\/span>| \u4f5c\u8005<\/strong><\/span><\/p>\n

\u9648\u65af\u4fe1<\/span> | \u8bd1\u8005<\/strong><\/span>
<\/p>\n

\u6881\u91d1<\/span> | \u5ba1\u6821<\/strong><\/span><\/strong><\/span><\/p>\n

\u9093\u4e00\u96ea<\/span> | \u7f16\u8f91<\/strong><\/span><\/strong><\/span><\/p>\n


<\/p>\n<\/section>\n


<\/p>\n

<\/p>\n

\n
\n
\n

\u8bba\u6587\u9898\u76ee\uff1a<\/span><\/p>\n

Collective Intelligence for Deep Learning: A Survey of Recent Developments<\/span><\/section>\n
\u8bba\u6587\u94fe\u63a5\uff1a<\/span><\/section>\n
https:\/\/arxiv.org\/abs\/2111.14377<\/span><\/section>\n<\/section>\n<\/section>\n<\/blockquote>\n

 <\/span>
<\/p>\n

\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n

\u76ee\u5f55<\/strong><\/p>\n


<\/p>\n

\n
<\/span><\/strong><\/section>\n

\u6458\u8981<\/span><\/strong><\/span><\/p>\n

\u4e00\u3001\u5f15\u8a00<\/span><\/strong><\/span><\/p>\n

\u4e8c\u3001\u5386\u53f2\u80cc\u666f<\/span><\/strong><\/span><\/p>\n

\u4e09\u3001\u6df1\u5ea6\u5b66\u4e60\u4e2d\u7684\u96c6\u4f53\u667a\u80fd<\/span><\/strong><\/span><\/p>\n

1\u3001\u56fe\u50cf\u5904\u7406<\/span><\/strong><\/span><\/p>\n

2\u3001\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60<\/span><\/strong><\/span><\/p>\n

3\u3001\u591a\u667a\u80fd\u4f53\u5b66\u4e60<\/span><\/strong><\/span><\/p>\n

4\u3001\u5143\u5b66\u4e60<\/span><\/strong><\/span><\/p>\n

\u56db\u3001\u5c06\u6df1\u5ea6\u5b66\u4e60\u7528\u4e8e\u96c6\u4f53\u667a\u80fd\u7814\u7a76<\/span><\/strong><\/span><\/p>\n

\u4e94\u3001\u7ed3\u8bba<\/span><\/strong><\/span><\/p>\n

<\/strong><\/strong><\/strong><\/span><\/span>
<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

<\/section>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u6458\u8981<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u5728\u8fc7\u53bb\u5341\u5e74\u91cc\uff0c\u6211\u4eec\u89c1\u8bc1\u4e86\u6df1\u5ea6\u5b66\u4e60\u5d1b\u8d77\u5e76\u5728\u4eba\u5de5\u667a\u80fd\u9886\u57df\u5360\u636e\u4e3b\u5bfc\u5730\u4f4d\u7684\u8fc7\u7a0b\u3002\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u8fdb\u6b65\uff0c\u4ee5\u53ca\u76f8\u5e94\u7684\u5177\u6709\u5927\u5185\u5b58\u5bb9\u91cf\u7684\u786c\u4ef6\u52a0\u901f\u5668\u7684\u53d1\u5c55\uff0c\u518d\u52a0\u4e0a\u5927\u578b\u6570\u636e\u96c6\u7684\u53ef\u5f97\u6027\uff0c\u4f7f\u5f97\u7814\u7a76\u4eba\u5458\u548c\u4ece\u4e1a\u4eba\u5458\u80fd\u591f\u8bad\u7ec3\u548c\u90e8\u7f72\u590d\u6742\u7684\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\uff0c\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u81ea\u7136\u8bed\u8a00\u5904\u7406\u548c\u5f3a\u5316\u5b66\u4e60\u7b49\u591a\u4e2a\u9886\u57df\u7684\u4efb\u52a1\u4e0a\u53d6\u5f97\u6700\u4f73\u6027\u80fd\u3002\u7136\u800c\uff0c\u968f\u7740\u8fd9\u4e9b\u795e\u7ecf\u7f51\u7edc\u53d8\u5f97\u66f4\u5927\u3001\u66f4\u590d\u6742\u3001\u5e94\u7528\u66f4\u5e7f\u6cdb\uff0c\u5f53\u524d\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u6839\u672c\u95ee\u9898\u53d8\u5f97\u66f4\u52a0\u660e\u663e\u3002\u4f17\u6240\u5468\u77e5\uff0c\u5f53\u524d\u6700\u5148\u8fdb\u7684\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u4e5f\u6709\u4e00\u4e9b\u95ee\u9898\uff0c\u5305\u62ec\u4e0d\u591f\u7a33\u5065\uff0c\u65e0\u6cd5\u9002\u5e94\u65b0\u7684\u4efb\u52a1\uff0c\u914d\u7f6e\u9700\u8981\u4e25\u683c\u548c\u4e0d\u7075\u6d3b\u7684\u5047\u8bbe\u7b49\u3002\u6765\u81ea\u96c6\u4f53\u667a\u80fd\u7684\u89c2\u5ff5\uff0c\u7279\u522b\u662f\u6765\u81ea\u590d\u6742\u7cfb\u7edf\u7684\u6982\u5ff5\uff0c\u5982\u81ea\u7ec4\u7ec7\u3001\u6d8c\u73b0\u884c\u4e3a\u3001\u7c92\u5b50\u7fa4\u4f18\u5316<\/span>\uff08swarm optimization\uff09<\/span>\u548c\u5143\u80de\u81ea\u52a8\u673a\uff0c\u5f80\u5f80\u4f1a\u4ea7\u751f\u7a33\u5065\u7684\u3001\u9002\u5e94\u6027\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u5e76\u4e14\u5bf9\u73af\u5883\u914d\u7f6e\u7684\u5047\u8bbe\u6ca1\u90a3\u4e48\u4e25\u683c\u3002\u56e0\u6b64\uff0c\u770b\u5230\u8fd9\u4e9b\u89c2\u5ff5\u88ab\u7eb3\u5165\u5230\u65b0\u7684\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u4e2d\uff0c\u5e76\u4e0d\u5947\u602a\u3002\u5728\u8fd9\u7bc7\u7efc\u8ff0\u91cc\uff0c\u6211\u4eec\u5c06\u63d0\u4f9b\u4e00\u4e2a\u6d89\u53ca\u590d\u6742\u7cfb\u7edf\u7684\u795e\u7ecf\u7f51\u7edc\u7814\u7a76\u7684\u5386\u53f2\u8109\u7edc\uff0c\u5e76\u7740\u91cd\u4e8e\u73b0\u4ee3\u6df1\u5ea6\u5b66\u4e60\u7814\u7a76\u4e2d\u51e0\u4e2a\u6d3b\u8dc3\u7684\u9886\u57df\uff0c\u8fd9\u4e9b\u9886\u57df\u7ed3\u5408\u4e86\u96c6\u4f53\u667a\u80fd\u7684\u539f\u7406\u6765\u63d0\u5347\u5f53\u524d\u6a21\u578b\u7684\u80fd\u529b\u3002\u4e3a\u4e86\u4fc3\u8fdb\u89c2\u5ff5\u7684\u53cc\u5411\u6d41\u52a8\uff0c\u6211\u4eec\u8fd8\u8ba8\u8bba\u4e86\u90a3\u4e9b\u5229\u7528\u73b0\u4ee3\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u6765\u5e2e\u52a9\u63a8\u8fdb\u590d\u6742\u7cfb\u7edf\u7814\u7a76\u7684\u7814\u7a76\u3002\u6211\u4eec\u5e0c\u671b\u8fd9\u7bc7\u7efc\u8ff0\u53ef\u4ee5\u6210\u4e3a\u590d\u6742\u7cfb\u7edf\u548c\u6df1\u5ea6\u5b66\u4e60\u793e\u533a\u4e4b\u95f4\u7684\u6865\u6881\uff0c\u4fc3\u8fdb\u89c2\u5ff5\u7684\u4ea4\u53c9\u4f20\u64ad\uff0c\u5e76\u4fc3\u8fdb\u8de8\u5b66\u79d1\u7684\u65b0\u5408\u4f5c\u3002<\/span><\/section>\n


<\/p>\n


<\/section>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u4e00\u3001\u5f15\u8a00<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u6df1\u5ea6\u5b66\u4e60<\/span>\uff08deep learning, DL\uff09<\/span>\u662f\u4e00\u7c7b\u4f7f\u7528\u591a\u5c42<\/span>\uff08\u201c\u6df1\u5ea6\u201d\uff09<\/span>\u795e\u7ecf\u7f51\u7edc\u8fdb\u884c\u8868\u5f81\u5b66\u4e60\u7684\u673a\u5668\u5b66\u4e60\u65b9\u6cd5\u3002\u65e9\u572820\u4e16\u7eaa80\u5e74\u4ee3\uff0c\u7528\u53cd\u5411\u4f20\u64ad\u7b97\u6cd5\u8bad\u7ec3\u7684\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u5c31\u51fa\u73b0\u4e86[57]\uff0c\u4f46\u76f4\u52302012\u5e74\uff0c\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u624d\u53d7\u5230\u5e7f\u6cdb\u5173\u6ce8\u3002\u5f53\u65f6\uff0c\u5728\u4e00\u5e74\u4e00\u5ea6\u7684\u56fe\u50cf\u8bc6\u522b\u6bd4\u8d5b\u4e2d\uff0c\u57fa\u4e8e\u5728GPU\u4e0a\u8bad\u7ec3\u7684\u6df1\u5ea6\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u65b9\u6cd5[35]\u4ee5\u663e\u8457\u4f18\u52bf\u6218\u80dc\u4e86\u4e0d\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u65b9\u6cd5\u3002\u8fd9\u6b21\u6210\u529f\u8868\u660e\uff0c\u5728\u6709\u786c\u4ef6\u52a0\u901f\u65b9\u6848\u4ee5\u53ca\u5927\u578b\u6570\u636e\u96c6\u7684\u60c5\u51b5\u4e0b\uff0c\u6df1\u5ea6\u5b66\u4e60\u80fd\u591f\u5728\u6709\u610f\u4e49\u7684\u4efb\u52a1\u4e2d\u53d6\u5f97\u6bd4\u4f20\u7edf\u65b9\u6cd5\u66f4\u597d\u7684\u7ed3\u679c\u3002\u7814\u7a76\u4eba\u5458\u548c\u4ece\u4e1a\u4eba\u5458\u5f88\u5feb\u5c31\u5f00\u59cb\u7528\u6df1\u5ea6\u5b66\u4e60\u6765\u89e3\u51b3\u5176\u5b83\u51e0\u4e2a\u9886\u57df\u4e00\u4e9b\u957f\u671f\u5b58\u5728\u7684\u95ee\u9898\uff0c\u5305\u62ec\u8ba1\u7b97\u673a\u89c6\u89c9<\/span>\uff08computer vision, CV\uff09<\/span>[24,47,60]\uff0c\u81ea\u7136\u8bed\u8a00\u5904\u7406<\/span>\uff08natural language processing, NLP\uff09<\/span>[5,48,49]\uff0c\u5f3a\u5316\u5b66\u4e60<\/span>\uff08reinforced learning, RL\uff09<\/span>[37,59,68]\u548c\u8ba1\u7b97\u751f\u7269\u5b66[32,58]\u7b49\uff1b\u5728\u8bb8\u591a\u9886\u57df\u91cc\uff0c\u90fd\u53d6\u5f97\u4e86\u6280\u672f\u4e0a\u7684\u7a81\u7834\u548c\u6700\u597d\u7684\u6548\u679c\u3002<\/span><\/section>\n
 <\/span><\/section>\n
<\/section>\n

\u56fe1. GPU\u786c\u4ef6\u7684\u8fd1\u671f\u53d1\u5c55\u4f7f\u6211\u4eec\u80fd\u5bf9\u6570\u4ee5\u5343\u8ba1\u7684\u673a\u5668\u4eba\u8fdb\u884c\u73b0\u5b9e\u4e09\u7ef4\u6a21\u62df\uff0c\u5c31\u50cf\u672c\u56fe\u6240\u5c55\u73b0\u7684Rudin\u7b49\u4eba\u6240\u505a\u7684\u4e00\u6837[53]\u3002\u8fd9\u6837\u7684\u8fdb\u6b65\u4f7f\u6211\u4eec\u80fd\u5bf9\u5927\u89c4\u6a21\u3001\u53ef\u4ee5\u8fdb\u884c\u4e92\u52a8\u5e76\u534f\u540c\u53d1\u5c55\u667a\u80fd\u884c\u4e3a\u7684\u7684\u4eba\u5de5\u667a\u80fd\u4f53\u8fdb\u884c\u4e09\u7ef4\u6a21\u62df\u3002<\/span><\/p>\n

 <\/span><\/section>\n
\u7136\u800c\uff0c\u6df1\u5ea6\u5b66\u4e60\u5e76\u4e0d\u662f\u6ca1\u6709\u526f\u4f5c\u7528\u7684\u7075\u4e39\u5999\u836f\u3002\u867d\u7136\u6211\u4eec\u89c1\u8bc1\u4e86\u8bb8\u591a\u6210\u529f\u7684\u6848\u4f8b\uff0c\u5e76\u4e14\u8d8a\u6765\u8d8a\u591a\u5730\u5728\u4f7f\u7528\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\uff0c\u4f46\u968f\u7740\u6a21\u578b\u548c\u8bad\u7ec3\u7b97\u6cd5\u53d8\u5f97\u8d8a\u6765\u8d8a\u5927\uff0c\u8d8a\u6765\u8d8a\u590d\u6742\uff0c\u6df1\u5ea6\u5b66\u4e60\u7684\u6839\u672c\u95ee\u9898\u4e5f\u8d8a\u6765\u8d8a\u660e\u663e\u5730\u66b4\u9732\u51fa\u6765\u3002\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u5e76\u4e0d\u7a33\u5065\u3002\u6bd4\u5982\uff0c\u5927\u5bb6\u90fd\u77e5\u9053\uff0c\u53ea\u8981\u4fee\u6539\u89c6\u9891\u6e38\u620f\u5c4f\u5e55\u4e0a\u7684\u51e0\u4e2a\u50cf\u7d20<\/span>\uff08\u8fd9\u79cd\u4fee\u6539\u4eba\u7c7b\u6839\u672c\u65e0\u6cd5\u5bdf\u89c9\uff09<\/span>\uff0c\u7528\u672a\u4fee\u6539\u7684\u5c4f\u5e55\u8bad\u7ec3\u51fa\u6765\u7684\u667a\u80fd\u4f53<\/span>\uff08\u539f\u672c\u8d85\u8fc7\u4eba\u7c7b\u8868\u73b0\uff09<\/span>\u5c31\u53ef\u80fd\u5931\u8d25[46]\u3002\u53e6\u5916\uff0c\u5728\u6ca1\u6709\u7279\u6b8a\u5904\u7406\u60c5\u51b5\u4e0b\u8bad\u7ec3\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u6a21\u578b\uff0c\u53ef\u80fd\u65e0\u6cd5\u8bc6\u522b\u65cb\u8f6c\u6216\u8005\u7ecf\u8fc7\u76f8\u4f3c\u53d8\u6362\u7684\u4f8b\u5b50\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u6211\u4eec\u76ee\u524d\u7684\u6a21\u578b\u548c\u8bad\u7ec3\u65b9\u6cd5\u5e76\u4e0d\u80fd\u81ea\u52a8\u6cdb\u5316\u5230\u65b0\u7684\u4efb\u52a1\u3002\u6700\u540e\u4f46\u540c\u6837\u91cd\u8981\u7684\u662f\uff0c\u5927\u591a\u6570\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u5e76\u4e0d\u80fd\u9002\u5e94\u53d8\u5316\u3002\u5b83\u4eec\u5047\u8bbe\u4e86\u56fa\u5b9a\u7684\u8f93\u5165\uff0c\u5e76\u9700\u8981\u56fa\u5b9a\u7684\u914d\u7f6e\u3002\u6bd4\u5982\uff0c\u5b83\u4eec\u53ef\u80fd\u9700\u8981\u56fa\u5b9a\u5927\u5c0f\uff0c\u56fa\u5b9a\u987a\u5e8f\u7684\u8f93\u5165\u3002\u5373\u4f7f\u8fd9\u4e9b\u6a21\u578b\u5df2\u7ecf\u5b66\u4f1a\u5e76\u5de9\u56fa\u4e86\u5b8c\u6210\u4efb\u52a1\u6240\u9700\u8981\u7684\u6280\u80fd\uff0c\u4e00\u65e6\u8fd9\u4e9b\u5047\u8bbe\u548c\u914d\u7f6e\u4e0d\u6210\u7acb\uff0c\u6a21\u578b\u4e5f\u4e0d\u4f1a\u6709\u597d\u7684\u8868\u73b0\uff0c\u9664\u975e\u6211\u4eec\u624b\u52a8\u8bad\u7ec3\u5b83\u4eec\uff0c\u6216\u8005\u624b\u52a8\u5904\u7406\u8f93\u5165\uff0c\u4f7f\u4e4b\u4e0e\u9884\u671f\u4e00\u81f4\u3002<\/span><\/section>\n

<\/section>\n
\u6765\u81ea\u96c6\u4f53\u667a\u80fd\uff08Collective Intelligence\uff0cCI\uff09\u7684\u6982\u5ff5\u503e\u5411\u4e8e\u4ea7\u751f\u7a33\u5065\u3001\u81ea\u9002\u5e94\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u5e76\u4e14\u5bf9\u73af\u5883\u914d\u7f6e\u7684\u5047\u8bbe\u6ca1\u90a3\u4e48\u4e25\u683c<\/span><\/strong>\u3002\u5c06\u8fd9\u4e9b\u6982\u5ff5\u5e94\u7528\u5230\u6df1\u5ea6\u5b66\u4e60\u4e4b\u4e2d\uff0c\u6709\u52a9\u4e8e\u81ea\u7136\u5730\u89e3\u51b3\u4e00\u4e9b\u95ee\u9898\u3002\u4e8b\u5b9e\u4e0a\uff0c\u8bb8\u591a\u53d7\u96c6\u4f53\u667a\u80fd\u542f\u53d1\u7684\u6982\u5ff5\u5df2\u7ecf\u5e7f\u4e3a\u4eba\u77e5\uff1b\u6700\u7b80\u5355\u7684\u5c06\u96c6\u4f53\u667a\u80fd\u7eb3\u5165\u6df1\u5ea6\u5b66\u4e60\u7684\u4f8b\u5b50\u662f\uff1a\u8bad\u7ec3\u4e00\u4e2a\u542b\u6709\u82e5\u5e72\u4e2a\u6a21\u578b\u7684\u96c6\u5408\uff0c\u5e76\u6839\u636e\u5e73\u5747\u8f93\u51fa\u8fdb\u884c\u9884\u6d4b\u3002\u8fd9\u7c7b\u4f3c\u4e8e\u6211\u4eec\u5728\u793e\u4f1a\u4e2d\u4f1a\u770b\u5230\u7684\u6295\u7968\u673a\u5236\u3002\u7136\u800c\uff0c\u4e2a\u4f53\u4e4b\u95f4\u7684\u6c9f\u901a\u6216\u5176\u5b83\u9ad8\u5c42\u6d3b\u52a8\uff0c\u901a\u5e38\u4e0d\u5728\u201c\u8f93\u51fa\u201d\u5c42\u9762\u8003\u8651\u6216\u5b9e\u65bd\u3002\u4e3a\u4e86\u5c06\u8fd9\u4e9b\u6d3b\u52a8\u4e5f\u7eb3\u5165\u8003\u8651\uff0c\u6df1\u5ea6\u5b66\u4e60\u548c\u96c6\u4f53\u667a\u80fd\u7684\u5176\u5b83\u7ec4\u5408\u91c7\u7eb3\u4e86\u590d\u6742\u7cfb\u7edf\u7684\u4e00\u4e9b\u6982\u5ff5\uff0c\u5982\u81ea\u7ec4\u7ec7\u3001\u6d8c\u73b0\u884c\u4e3a\u3001\u7c92\u5b50\u7fa4\u4f18\u5316\u548c\u5143\u80de\u81ea\u52a8\u673a\u3002\u7531\u6b64\u4ea7\u751f\u7684\u7cfb\u7edf\uff0c\u5df2\u7ecf\u88ab\u8bc1\u660e\u662f\u4e0a\u4e00\u6bb5\u6240\u8ff0\u67d0\u4e9b\u95ee\u9898\u7684\u6f5c\u5728\u89e3\u51b3\u65b9\u6848\u3002\u4f8b\u5982\uff0c\u57fa\u4e8e\u5143\u80de\u81ea\u52a8\u673a\u7684\u795e\u7ecf\u7f51\u7edc\u53ef\u4ee5\u62b5\u6297\u566a\u97f3\uff0c\u751a\u81f3\u5728\u635f\u574f\u65f6\u201c\u81ea\u6211\u4fee\u590d\u201d[38]\u3002\u53e6\u4e00\u4e2a\u4f8b\u5b50\u662f\uff0c\u6a21\u5757\u5316\u3001\u53bb\u4e2d\u5fc3\u5316\u7684\u81ea\u7ec4\u7ec7\u63a7\u5236\u5668\uff0c\u4e0d\u4ec5\u5c55\u73b0\u4e86\u901a\u7528\u63a7\u5236\u5668\u7684\u53ef\u80fd\u6027\uff0c\u800c\u4e14\u5728\u90e8\u7f72\u5728\u591a\u4e2a\u4e0d\u540c\u5f62\u6001\u7684\u673a\u5668\u4eba\u4e0a\u65f6<\/span>\uff08\u5728\u6a21\u62df\u4e2d\uff09<\/span>\u4e5f\u80fd\u4fdd\u6301\u6027\u80fd[29]\u3002\u901a\u8fc7\u5c06\u6bcf\u4e2a\u611f\u89c9\u795e\u7ecf\u5143\u5efa\u6a21\u4e3a\u4e00\u4e2a\u5355\u72ec\u7684\u795e\u7ecf\u7f51\u7edc\uff0c\u5e76\u5141\u8bb8\u8fd9\u4e9b\u795e\u7ecf\u7f51\u7edc\u4e92\u76f8\u901a\u4fe1\uff0c\u62e5\u6709\u8fd9\u4e2a\u5c42\u7684\u6a21\u578b\u80fd\u591f\u5904\u7406\u4efb\u610f\u5927\u5c0f\uff0c\u4efb\u610f\u987a\u5e8f\u7684\u8f93\u5165[65]\u3002\u6700\u540e\uff0c\u56fe1\u5c55\u73b0\u4e86\u5728\u5355\u4e2aGPU\u4e0a\u540c\u65f6\u8bad\u7ec3\u51e0\u5343\u4e2a\u5f3a\u5316\u5b66\u4e60\u667a\u80fd\u4f53\u7684\u7ed3\u679c[53]\u3002\u968f\u7740\u786c\u4ef6\u52a0\u901f\u6280\u672f\u7684\u4e0d\u65ad\u8fdb\u6b65\uff0c\u6211\u4eec\u5f53\u7136\u53ef\u4ee5\u671f\u5f85\u770b\u5230\u66f4\u591a\uff0c\u5c06\u96c6\u4f53\u667a\u80fd\u7684\u6982\u5ff5\u878d\u5165\u57fa\u4e8e\u7fa4\u4f53\u7684\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u7684\u7814\u7a76\u3002\u8fd9\u7bc7\u7efc\u8ff0\u7684\u76ee\u7684\u662f\u5bf9\u6700\u8fd1\u5728\u6df1\u5ea6\u5b66\u4e60\u8303\u5f0f\u4e2d\u5229\u7528\u4e86\u201c\u81ea\u7ec4\u7ec7\u201d\u548c\u201c\u6d8c\u73b0\u884c\u4e3a\u201d\u7b49\u6982\u5ff5\u7684\u7814\u7a76\u8fdb\u884c\u8c03\u7814<\/strong>\u3002\u53cd\u8fc7\u6765\uff0c\u7528\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u6765\u5206\u6790\u4f20\u7edf\u7684\u5143\u80de\u81ea\u52a8\u673a\u7cfb\u7edf\u4e5f\u5f88\u6709\u7528\uff0c\u867d\u7136\u8fd9\u4e0d\u662f\u672c\u6587\u7684\u91cd\u70b9\uff0c\u4f46\u6211\u4eec\u4e5f\u4f1a\u8ba8\u8bba\u3002\u867d\u7136\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u7814\u7a76\u8303\u5f0f\u5c42\u51fa\u4e0d\u7a77\uff0c\u4f46\u4e8b\u5b9e\u8bc1\u660e\uff0c\u8981\u8fdb\u4e00\u6b65\u7406\u89e3\u66f4\u91cd\u8981\u7684\u95ee\u9898<\/span>\uff08\u4f8b\u5982\u4e0d\u540c\u65f6\u95f4\u5c3a\u5ea6\u7684\u5168\u7403\u6c14\u5019\u53d8\u5316\u6a21\u578b\uff09<\/span>\uff0c\u5c31\u66f4\u9700\u8981\u6765\u81ea\u590d\u6742\u7cfb\u7edf\u9886\u57df\u7684\u6838\u5fc3\u89c2\u5ff5\u3002\u6211\u4eec\u5c06\u770b\u5230\uff0c\u4e0d\u7ba1\u6211\u4eec\u76ee\u524d\u7684\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u5904\u4e8e\u4f55\u79cd\u8303\u5f0f\uff0c\u603b\u6709\u4e00\u4e9b\u89c2\u5ff5\u662f\u53ef\u4ee5\u5e94\u7528\u7684\u3002<\/span><\/section>\n
 <\/span><\/section>\n
 <\/span><\/section>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u4e8c\u3001\u5386\u53f2\u80cc\u666f<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u6765\u81ea\u590d\u6742\u7cfb\u7edf\u9886\u57df\u7684\u6982\u5ff5\u548c\u89c2\u5ff5\uff0c\u5982\u5143\u80de\u81ea\u52a8\u673a<\/span>\uff08cellular automata, CA\uff09<\/span>\u3001\u81ea\u7ec4\u7ec7\u3001\u6d8c\u73b0\u4e0e\u96c6\u4f53\u884c\u4e3a\uff0c\u4e0e\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u6709\u7740\u60a0\u4e45\u800c\u6709\u8da3\u7684\u5386\u53f2\u5173\u7cfb\u3002\u867d\u7136\u8fde\u63a5\u4e3b\u4e49\u548c\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u662f\u572820\u4e16\u7eaa50\u5e74\u4ee3\uff0c\u968f\u7740\u4eba\u5de5\u667a\u80fd\u4f5c\u4e3a\u4e00\u4e2a\u7814\u7a76\u9886\u57df\u7684\u8bde\u751f\u800c\u51fa\u73b0\u7684\uff0c\u4f46\u6211\u4eec\u7684\u6545\u4e8b\u5f00\u59cb\u4e8e20\u4e16\u7eaa70\u5e74\u4ee3\u3002\u5f53\u65f6\uff0c\u5148\u9a71Leon Chua\u9886\u5bfc\u4e86\u4e00\u7fa4\u7535\u5b50\u5de5\u7a0b\u5e08\uff0c\u5f00\u59cb\u53d1\u5c55\u975e\u7ebf\u6027\u7535\u8def\u7406\u8bba\uff0c\u5e76\u5c06\u5176\u5e94\u7528\u4e8e\u8ba1\u7b97\u3002\u4ed6\u56e0\u572820\u4e16\u7eaa70\u5e74\u4ee3\u6784\u601d\u4e86\u5fc6\u963b\u5668<\/span>\uff08Memristor\uff0c\u4e00\u79cd\u6700\u8fd1\u624d\u5b9e\u73b0\u7684\u7535\u5b50\u5668\u4ef6\uff09<\/span>\u4ee5\u53ca\u8521\u6c0f\u7535\u8def<\/span>\uff08Chua circuit\uff0c\u6700\u65e9\u6709\u6df7\u6c8c\u884c\u4e3a\u7684\u7535\u8def\u4e4b\u4e00\uff09<\/span>\u800c\u95fb\u540d\u3002\u572820\u4e16\u7eaa80\u5e74\u4ee3\uff0c\u4ed6\u7684\u56e2\u961f\u5f00\u53d1\u4e86\u5143\u80de\u795e\u7ecf\u7f51\u7edc<\/strong><\/span>\uff08Cellular Neural Network, CeNNs\uff09<\/span>\uff0c\u8fd9\u662f\u4e00\u79cd\u7c7b\u4f3c\u4e8e\u5143\u80de\u81ea\u52a8\u673a\u7684\u8ba1\u7b97\u7cfb\u7edf\uff0c\u4f46\u4f7f\u7528\u795e\u7ecf\u7f51\u7edc\u6765\u4ee3\u66ff\u5143\u80de\u81ea\u52a8\u673a\u7cfb\u7edf<\/span>\uff08\u5982\u5eb7\u5a01\u751f\u547d\u6e38\u620f[14]\u6216Wolfram\u7684\u521d\u7b49\u5143\u80de\u81ea\u52a8\u673a[70]\uff09<\/span>\u4e2d\u5178\u578b\u7684\u7b97\u6cd5\u5355\u5143\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u5143\u80de\u795e\u7ecf\u7f51\u7edc[11,12]\u662f\u4e00\u79cd\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff0c\u91cc\u9762\u7684\u6bcf\u4e2a\u795e\u7ecf\u5143\u6216\u5143\u80de\u53ea\u80fd\u548c\u5b83\u4eec\u7684\u8fd1\u90bb\u4e92\u52a8\u3002\u5728\u6700\u57fa\u672c\u7684\u8bbe\u7f6e\u91cc\uff0c\u6bcf\u4e2a\u5143\u80de\u7684\u72b6\u6001\u7528\u4e00\u4e2a\u57fa\u4e8e\u5176\u90bb\u5c45\u72b6\u6001\u548c\u81ea\u8eab\u72b6\u6001\u7684\u975e\u7ebf\u6027\u51fd\u6570\u6301\u7eed\u66f4\u65b0\u3002\u4e0e\u4f9d\u8d56\u6570\u5b57\u5316\u3001\u79bb\u6563\u5316\u8ba1\u7b97\u7684\u73b0\u4ee3\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u4e0d\u540c\uff0c\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u662f\u65f6\u95f4\u4e0a\u8fde\u7eed\u7684\u7cfb\u7edf\uff0c\u53ef\u4ee5\u7528\u975e\u7ebf\u6027\u7535\u5b50\u5143\u4ef6\u5b9e\u73b0\u9ad8\u901f\u6a21\u62df\u8ba1\u7b97<\/strong><\/span>\uff08\u5c3d\u7ba1\u5176\u65f6\u95f4\u79bb\u6563\u7248\u672c\u540e\u6765\u5df2\u7ecf\u7528FPGA\u786c\u4ef6\u5b9e\u73b0[39]\uff09<\/span>\u3002\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u7684\u52a8\u6001\u6f14\u5316\u4f9d\u8d56\u4e8e\u72ec\u7acb\u3001\u5c40\u90e8\u7684\u4fe1\u606f\u5904\u7406\uff0c\u4ee5\u53ca\u5904\u7406\u5355\u5143\u4e4b\u95f4\u7684\u4e92\u52a8\u3002\u4e0e\u5143\u80de\u81ea\u52a8\u673a\u4e00\u6837\uff0c\u5b83\u4eec\u4e5f\u8868\u73b0\u51fa\u4e86\u6d8c\u73b0\u884c\u4e3a\uff0c\u5e76\u4e14\u53ef\u4ee5\u88ab\u505a\u6210\u901a\u7528\u56fe\u7075\u673a\u3002\u7136\u800c\uff0c\u5b83\u4eec\u6bd4\u79bb\u6563\u7684\u5143\u80de\u81ea\u52a8\u673a\u548c\u6570\u5b57\u8ba1\u7b97\u673a\u8981\u901a\u7528\u5f97\u591a\u3002\u7531\u4e8e\u8fde\u7eed\u7684\u72b6\u6001\u7a7a\u95f4\uff0c\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u8868\u73b0\u51fa\u524d\u6240\u672a\u6709\u7684\u6d8c\u73b0\u884c\u4e3a\u3002[20]<\/span><\/section>\n
 <\/span><\/section>\n
\u4ece1990\u5e74\u4ee3\u52302000\u5e74\u4ee3\u4e2d\u671f\uff0c\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u6210\u4e3a\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u7684\u4e00\u4e2a\u5b50\u9886\u57df\u3002\u7531\u4e8e\u5176\u5f3a\u5927\u800c\u9ad8\u6548\u7684\u5206\u5e03\u5f0f\u8ba1\u7b97\u80fd\u529b\uff0c\u5b83\u88ab\u5e94\u7528\u5230\u56fe\u50cf\u5904\u7406\u548c\u7eb9\u7406\u5206\u6790\u4e2d\u3002\u7531\u4e8e\u5176\u4e0e\u751f\u4ff1\u6765\u7684\u6a21\u62df\u8ba1\u7b97\u80fd\u529b\uff0c\u5b83\u4e5f\u88ab\u5e94\u7528\u4e8e\u504f\u5fae\u5206\u65b9\u7a0b\u7684\u6c42\u89e3\uff0c\u751a\u81f3\u662f\u751f\u7269\u7cfb\u7edf\u548c\u5668\u5b98\u7684\u5efa\u6a21\u3002\u5173\u4e8e\u5143\u80de\u795e\u7ecf\u7f51\u7edc\uff0c\u6709\u6570\u4ee5\u5343\u8ba1\u7684\u540c\u884c\u8bc4\u8bae\u8bba\u6587\u3001\u6559\u79d1\u4e66\uff0c\u4ee5\u53ca\u4e00\u4e2a\u4e13\u95e8\u8ba8\u8bba\u7684IEEE\u4f1a\u8bae\uff0c\u8fd8\u6709\u8bb8\u591a\u6269\u5927\u3001\u5806\u53e0\u5b83\u4eec\uff0c\u5c06\u5b83\u4eec\u4e0e\u6570\u5b57\u7535\u8def\u7ed3\u5408\u7684\u63d0\u8bae\uff0c\u4ee5\u53ca\u5bf9\u4e0d\u540c\u8bad\u7ec3\u65b9\u6cd5\u7684\u7814\u7a76<\/span>\uff08\u5c31\u50cf\u6211\u4eec\u76ee\u524d\u5728\u6df1\u5ea6\u5b66\u4e60\u4e2d\u770b\u5230\u7684\u90a3\u6837\uff09<\/span>\u3002\u81f3\u5c11\u6709\u4e24\u5bb6\u786c\u4ef6\u521d\u521b\u516c\u53f8\u6210\u7acb\uff0c\u6765\u751f\u4ea7\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u7684\u786c\u4ef6\u4e0e\u8bbe\u5907\u3002\u7136\u800c\uff0c\u57282000\u5e74\u4ee3\u540e\u671f\uff0c\u5b83\u4eec\u7a81\u7136\u4ece\u821e\u53f0\u4e0a\u6d88\u5931\u4e86\u30022006\u5e74\u4ee5\u540e\uff0c\u4eba\u5de5\u667a\u80fd\u754c\u51e0\u4e4e\u4e0d\u518d\u63d0\u53ca\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u3002\u800c\u4ece2010\u5e74\u4ee3\u5f00\u59cb\uff0cGPU\u6210\u4e3a\u795e\u7ecf\u7f51\u7edc\u7814\u7a76\u7684\u4e3b\u8981\u5e73\u53f0\uff0c\u795e\u7ecf\u7f51\u7edc\u4e5f\u6539\u5934\u6362\u9762\u4e3a\u6df1\u5ea6\u5b66\u4e60\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6ca1\u6709\u4eba\u771f\u7684\u77e5\u9053\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u5728\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u4e2d\u6d88\u4ea1\u7684\u786e\u5207\u539f\u56e0\u3002\u4e5f\u8bb8\u662f\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u9886\u5148\u4e8e\u5b83\u7684\u65f6\u4ee3<\/span>\uff08\u5c31\u50cf\u5fc6\u963b\u5668\u4e00\u6837\uff09<\/span>\uff0c\u4e5f\u8bb8\u662f\u6d88\u8d39\u7ea7GPU\u7684\u5d1b\u8d77\u4f7fGPU\u6210\u4e3a\u4e00\u4e2a\u5f15\u4eba\u6ce8\u76ee\u7684\u6df1\u5ea6\u5b66\u4e60\u5e73\u53f0\u3002\u4eba\u4eec\u53ea\u80fd\u60f3\u50cf\uff0c\u5728\u4e00\u4e2a\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u7684\u6a21\u62df\u8ba1\u7b97\u673a\u82af\u7247\u8d62\u5f97\u786c\u4ef6\u5f69\u7968\u7684\u5e73\u884c\u5b87\u5b99\u91cc\uff0c\u4eba\u5de5\u667a\u80fd\u7684\u72b6\u6001\u53ef\u80fd\u4f1a\u975e\u5e38\u4e0d\u540c\u3002\u5728\u90a3\u4e2a\u5b87\u5b99\u91cc\uff0c\u4e16\u754c\u548c\u6211\u4eec\u6240\u6709\u7684\u8bbe\u5907\uff0c\u90fd\u5d4c\u5165\u4e86\u5f3a\u5927\u7684\u5206\u5e03\u5f0f\u7684\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u7136\u800c\uff0c\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u4e00\u4e2a\u5173\u952e\u533a\u522b\u662f\u524d\u8005\u4f7f\u7528\u4e0d\u591f\u65b9\u4fbf\uff0c\u5728\u6211\u4eec\u770b\u6765\uff0c\u8fd9\u662f\u5b83\u6ca1\u6709\u6d41\u884c\u8d77\u6765\u7684\u4e3b\u8981\u539f\u56e0\u3002\u5728\u76ee\u524d\u7684\u6df1\u5ea6\u5b66\u4e60\u8303\u5f0f\u4e2d\uff0c\u6709\u4e00\u4e2a\u5b8c\u6574\u7684\u5de5\u5177\u751f\u6001\u7cfb\u7edf\uff0c\u65e8\u5728\u7b80\u5316\u795e\u7ecf\u7f51\u7edc\u7684\u8bad\u7ec3\u548c\u90e8\u7f72\u3002\u7528\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u6765\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc\u4e5f\u662f\u76f8\u5bf9\u76f4\u63a5\u7684\uff0c\u53ea\u8981\u7ed9\u5b83\u63d0\u4f9b\u4e00\u4e2a\u6570\u636e\u96c6[9]\u6216\u8005\u4e00\u4e2a\u6a21\u62df\u7684\u4efb\u52a1\u73af\u5883[26]\u3002\u6df1\u5ea6\u5b66\u4e60\u5de5\u5177\u88ab\u8bbe\u8ba1\u6210\u4efb\u4f55\u4e00\u4e2a\u6709\u57fa\u672c\u7f16\u7a0b\u80cc\u666f\u7684\u4eba\u90fd\u53ef\u4ee5\u4f7f\u7528\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0c\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u662f\u4e3a\u7535\u5b50\u5de5\u7a0b\u5e08\u8bbe\u8ba1\u7684\uff0c\u6bd5\u7adf\u5728\u90a3\u4e2a\u5e74\u4ee3\uff0c\u7535\u5b50\u5de5\u7a0b\u7684\u5b66\u751f\u5bf9\u6a21\u62df\u7535\u8def\u7684\u4e86\u89e3\u591a\u4e8e\u7f16\u7a0b\u8bed\u8a00\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u4e3a\u4e86\u8bf4\u660e\u8fd9\u4e00\u56f0\u96be\uff0c\u201c\u8bad\u7ec3\u201d\u4e00\u4e2a\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u9700\u8981\u89e3\u4e00\u4e2a\u81f3\u5c11\u67099\u4e2a\u5e38\u5fae\u5206\u65b9\u7a0b\u7684\u7cfb\u7edf\uff0c\u6765\u51b3\u5b9a\u652f\u914d\u6a21\u62df\u7535\u8def\u7684\u7cfb\u6570\uff0c\u4ece\u800c\u5b9a\u4e49\u7cfb\u7edf\u7684\u884c\u4e3a\u3002\u5728\u5b9e\u8df5\u4e2d\uff0c\u8bb8\u591a\u4ece\u4e1a\u8005\u9700\u8981\u4f9d\u8d56\u4e00\u672c\u5305\u542b\u5df2\u77e5\u95ee\u9898\u7684\u89e3\u51b3\u65b9\u6848\u7684\u624b\u518c[10]\uff0c\u7136\u540e\u4e3a\u65b0\u95ee\u9898\u8c03\u6574\u89e3\u51b3\u65b9\u6848\u3002\u540e\u6765\uff0c\u4eba\u4eec\u63d0\u51fa\u9057\u4f20\u7b97\u6cd5<\/span>\uff08\u4ee5\u53ca\u65e9\u671f\u7248\u672c\u7684\u53cd\u5411\u4f20\u64ad\uff09<\/span>\u6765\u8bad\u7ec3\u5143\u80de\u795e\u7ecf\u7f51\u7edc[34]\uff0c\u4f46\u7535\u8def\u9700\u8981\u6a21\u62df\u8f6f\u4ef6\u6765\u8bad\u7ec3\u548c\u6d4b\u8bd5\uff0c\u624d\u80fd\u90e8\u7f72\u5230\u5b9e\u9645\u7684<\/span>\uff08\u9ad8\u5ea6\u5b9a\u5236\u7684\uff09<\/span>\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u786c\u4ef6\u4e0a\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6211\u4eec\u4e5f\u8bb8\u53ef\u4ee5\u4ece\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u4e2d\u5b66\u5230\u66f4\u591a\uff0c\u6bd5\u7adf\u5b83\u4eec\u662f\u6a21\u62df\u548c\u6570\u5b57\u8ba1\u7b97\u7684\u5f3a\u5927\u6df7\u5408\u4f53\uff0c\u771f\u6b63\u5730\u7ed3\u5408\u4e86\u5143\u80de\u81ea\u52a8\u673a\u548c\u795e\u7ecf\u7f51\u7edc\u3002\u4e0d\u5e78\u7684\u662f\uff0c\u5728\u5b83\u4eec\u6d88\u4ea1\u4e4b\u524d\uff0c\u6211\u4eec\u89c1\u8bc1\u7684\u53ef\u80fd\u53ea\u662f\u5176\u5168\u90e8\u6f5c\u529b\u7684\u4e00\u5c0f\u90e8\u5206\u3002\u540e\u6765\uff0c\u5546\u54c1\u5316\u7684GPU\uff0c\u4ee5\u53ca\u5c06\u795e\u7ecf\u7f51\u7edc\u62bd\u8c61\u4e3a\u7b80\u5355\u7684Python\u4ee3\u7801\u7684\u5de5\u5177\uff0c\u4f7f\u6df1\u5ea6\u5b66\u4e60\u80fd\u591f\u63a5\u7ba1\u3002\u867d\u7136\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u5df2\u7ecf\u6d88\u5931\u4e86\uff0c\u4f46\u6765\u81ea\u590d\u6742\u7cfb\u7edf\u7684\u6982\u5ff5\u548c\u89c2\u5ff5\uff0c\u5982\u5143\u80de\u81ea\u52a8\u673a\u3001\u81ea\u7ec4\u7ec7\u548c\u6d8c\u73b0\u884c\u4e3a\uff0c\u5e76\u6ca1\u6709\u6d88\u5931\u3002\u6211\u4eec\u6b63\u5728\u89c1\u8bc1\u96c6\u4f53\u667a\u80fd\u7684\u6982\u5ff5\u5728\u6df1\u5ea6\u5b66\u4e60\u7684\u8bb8\u591a\u9886\u57df\u91cd\u73b0\u51fa\u73b0<\/span>\uff08\u5c3d\u7ba1\u4ec5\u9650\u4e8e\u6570\u5b57\u786c\u4ef6\uff09<\/span>\uff0c\u4ece\u56fe\u50cf\u751f\u6210\u3001\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\uff0c\u5230\u7fa4\u4f53\u5f0f\u548c\u5206\u5e03\u5f0f\u5b66\u4e60\u7b97\u6cd5\u3002\u6b63\u5982\u4e0b\u6587\u5c06\u5448\u73b0\u7684\uff0c\u8fd9\u4e9b\u6982\u5ff5\u6b63\u5728\u4e3a\u4f20\u7edf\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u4e00\u4e9b\u5c40\u9650\u548c\u9650\u5236\u63d0\u4f9b\u89e3\u51b3\u65b9\u6848\uff0c\u4ece\u800c\u63a8\u8fdb\u6df1\u5ea6\u5b66\u4e60\u7684\u7814\u7a76\u3002<\/span><\/section>\n
 <\/span><\/section>\n

<\/span><\/section>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u4e09\u3001\u96c6\u4f53\u667a\u80fd\u7528\u4e8e\u6df1\u5ea6\u5b66\u4e60<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u96c6\u4f53\u667a\u80fd\u4ece\u7f51\u7edc\u4e2d\u81ea\u7136\u4ea7\u751f\uff0c\u56e0\u6b64\uff0c\u770b\u5230\u81ea\u7ec4\u7ec7\u884c\u4e3a\u5728\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u4e2d\u81ea\u7136\u6d8c\u73b0\uff0c\u4e5f\u5c31\u4e0d\u5947\u602a\u4e86\uff0c\u5c24\u5176\u662f\u5f53\u6211\u4eec\u5728\u5168\u5c40\u8303\u56f4\u91c7\u7528\u6709\u7740\u76f8\u540c\u6743\u91cd\u7684\u76f8\u540c\u6a21\u5757\u8fdb\u884c\u91cd\u590d\u8ba1\u7b97\u65f6\u3002\u4f8b\u5982\uff0cGilpin[19]\u89c2\u5bdf\u5230\u5143\u80de\u81ea\u52a8\u673a\u548c\u5377\u79ef\u795e\u7ecf\u7f51\u7edc<\/span>\uff08convolutional neural networks, CNNs\uff0c\u4e00\u79cd\u5e38\u7528\u4e8e\u56fe\u50cf\u5904\u7406\u7684\u795e\u7ecf\u7f51\u7edc\uff0c\u5bf9\u6240\u6709\u7684\u8f93\u5165\u90fd\u91c7\u53d6\u76f8\u540c\u7684\u6743\u91cd\uff08\u6216\u8fc7\u6ee4\u5668\uff09\uff09<\/span>\u4e4b\u95f4\u7684\u5bc6\u5207\u8054\u7cfb\u3002\u4e8b\u5b9e\u4e0a\uff0c\u4ed6\u4eec\u8868\u660e\uff0c\u4efb\u4f55\u5143\u80de\u81ea\u52a8\u673a\u90fd\u53ef\u4ee5\u7528\u67d0\u79cd\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u6765\u8868\u793a\uff0c\u5e76\u4e14\u7528\u5b83\u4f18\u96c5\u5730\u6f14\u793a\u4e86\u5eb7\u5a01\u751f\u547d\u6e38\u620f[14]\uff0c\u8bf4\u660e\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u53ef\u4ee5\u8868\u73b0\u51fa\u6709\u8da3\u7684\u81ea\u7ec4\u7ec7\u884c\u4e3a<\/strong>\u3002\u8fd1\u671f\u7684\u4e00\u4e9b\u7814\u7a76\uff0c\u4f8b\u5982Mordintsev\u7b49\u4eba\u7684\u5de5\u4f5c[38]<\/span>\uff08\u6211\u4eec\u5c06\u5728\u540e\u9762\u8ba8\u8bba\uff09<\/span>\uff0c\u5229\u7528\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7684\u81ea\u7ec4\u7ec7\u7279\u6027\uff0c\u5e76\u5f00\u53d1\u4e86\u57fa\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u5143\u80de\u81ea\u52a8\u673a\uff0c\u5e94\u7528\u4e8e\u56fe\u50cf\u518d\u751f\u7b49\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u5176\u5b83\u7c7b\u578b\u7684\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\uff0c\u5982\u56fe\u795e\u7ecf\u7f51\u7edc<\/strong><\/span>\uff08Graph Neural Networks\uff0cGNNs\uff09<\/span>[54,71]\u660e\u786e\u5730\u4ee5\u81ea\u7ec4\u7ec7\u4e3a\u4e2d\u5fc3\u7279\u5f81<\/strong>\uff0c\u5c06\u56fe\u7684\u6bcf\u4e2a\u8282\u70b9<\/span>\uff08node\uff09<\/span>\u7684\u884c\u4e3a\uff0c\u5efa\u6a21\u4e3a\u76f8\u540c\u7684\u795e\u7ecf\u7f51\u7edc\u6a21\u5757\uff0c\u8be5\u6a21\u5757\u5c06\u4fe1\u606f\u4f20\u9012\u7ed9\u7531\u56fe\u7684\u8fb9<\/span>\uff08edge\uff09<\/span>\u6240\u5b9a\u4e49\u7684\u90bb\u5c45\u3002\u4f20\u7edf\u4e0a\uff0c\u56fe\u795e\u7ecf\u7f51\u7edc\u88ab\u7528\u6765\u5206\u6790\u56fe\uff0c\u4f8b\u5982\u793e\u4f1a\u7f51\u7edc\u548c\u5206\u5b50\u7ed3\u6784\u3002\u800c\u8fd1\u671f\u7684\u7814\u7a76[21]\u4e5f\u8bc1\u660e\u56fe\u795e\u7ecf\u7f51\u7edc\u6709\u80fd\u529b\u4e3a\u65e2\u5b9a\u7684\u5143\u80de\u81ea\u52a8\u673a\u7cfb\u7edf<\/span>\uff08\u4f8b\u5982\u7ef4\u8bfa\u56fe\u6216\u8702\u7fa4\u7684\u6210\u7fa4\u884c\u4e3a\uff09<\/span>\u5b66\u4e60\u89c4\u5219\u3002\u6b63\u5982\u6211\u4eec\u5c06\u5728\u540e\u9762\u8ba8\u8bba\u7684\u90a3\u6837\uff0c\u56fe\u795e\u7ecf\u7f51\u7edc\u7684\u81ea\u7ec4\u7ec7\u7279\u6027\u6700\u8fd1\u88ab\u7528\u4e8e\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u9886\u57df\uff0c\u521b\u9020\u51fa\u6709\u66f4\u5f3a\u6cdb\u5316\u80fd\u529b\u7684\u667a\u80fd\u4f53\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6211\u4eec\u5df2\u7ecf\u8bc6\u522b\u51fa\u4e86\u6df1\u5ea6\u5b66\u4e60\u7684\u56db\u4e2a\u9886\u57df\uff0c\u8fd9\u56db\u4e2a\u9886\u57df\u5df2\u7ecf\u5f00\u59cb\u5c06\u96c6\u4f53\u667a\u80fd\u76f8\u5173\u7684\u89c2\u5ff5\u7eb3\u5165\u8003\u8651\u3002\uff081\uff09\u56fe\u50cf\u5904\u7406\uff0c\uff082\uff09\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\uff0c\uff083\uff09\u591a\u667a\u80fd\u4f53\u5b66\u4e60\uff0c\u4ee5\u53ca\uff084\uff09\u5143\u5b66\u4e60\u3002\u6211\u4eec\u5c06\u5728\u672c\u8282\u4e2d\u8be6\u7ec6\u63a2\u8ba8\u6bcf\u4e2a\u9886\u57df\u5e76\u63d0\u4f9b\u4f8b\u5b50\u3002<\/span><\/section>\n
 <\/span><\/section>\n
<\/section>\n

\u56fe2. Randazzo\u7b49\u4eba\u521b\u5efa\u7684\u7528\u4e8e\u8bc6\u522bMNIST\u6570\u5b57\u7684\u795e\u7ecf\u5143\u80de\u81ea\u52a8\u673a[50]\u8fd8\u6709\u4e00\u4e2a\u5728\u7ebf\u7684\u53ef\u4e92\u52a8\u7684\u6f14\u793a\u7a0b\u5e8f\u3002\u6bcf\u4e2a\u5143\u80de\u53ea\u5141\u8bb8\u770b\u5230\u4e00\u4e2a\u50cf\u7d20\u7684\u5185\u5bb9\uff0c\u5e76\u4e0e\u5b83\u7684\u90bb\u5c45\u4ea4\u6d41\u3002\u968f\u7740\u65f6\u95f4\u63a8\u79fb\uff0c\u8fd9\u4e9b\u5143\u80de\u5c06\u5c31\u54ea\u4e2a\u6570\u5b57\u662f\u6700\u6709\u53ef\u80fd\u7684\u5f62\u6210\u5171\u8bc6\u3002\u4f46\u6709\u8da3\u7684\u662f\uff0c\u5206\u6b67\u8fd8\u662f\u4f1a\u56e0\u4e3a\u50cf\u7d20\u4f4d\u7f6e\u800c\u4ea7\u751f\uff0c\u7279\u522b\u662f\u5728\u56fe\u50cf\u6545\u610f\u7cc5\u5408\u4e86\u4e0d\u540c\u6570\u5b57\u7684\u65f6\u5019\u3002<\/span><\/p>\n

 <\/span><\/section>\n

\n
1\u3001\u56fe\u50cf\u5904\u7406<\/span><\/strong><\/span><\/section>\n<\/h4>\n

<\/section>\n
\u91c7\u7528\u5143\u80de\u81ea\u52a8\u673a\u7684\u65b9\u6cd5\u6765\u5b66\u4e60\u56fe\u50cf\u7684\u66ff\u4ee3\u8868\u793a\uff0c\u6709\u52a9\u4e8e\u5b66\u5230\u81ea\u7136\u5a92\u4ecb\u4e2d\u7684\u9690\u542b\u5173\u7cfb\u548c\u91cd\u590d\u51fa\u73b0\u7684\u6a21\u5f0f\u3002Mordvintsev\u7b49\u4eba\u63d0\u51fa\u7684\u795e\u7ecf\u5143\u80de\u81ea\u52a8\u673a<\/strong><\/span>\uff08neural CA\uff09<\/span>\u6a21\u578b[38]\uff0c\u548c\u5143\u80de\u795e\u7ecf\u7f51\u7edc\u4e00\u6837\uff0c\u5c06\u56fe\u50cf\u7684\u6bcf\u4e2a\u50cf\u7d20\u89c6\u4e3a\u4e00\u4e2a\u5355\u72ec\u7684\u795e\u7ecf\u7f51\u7edc\u5143\u80de\u3002\u8fd9\u4e9b\u7f51\u7edc\u88ab\u8bad\u7ec3\u6210\u6839\u636e\u5176\u8fd1\u90bb\u7684\u72b6\u6001\u6765\u9884\u6d4b\u5176\u989c\u8272\uff0c\u4ece\u800c\u5f62\u6210\u4e86\u4e00\u4e2a\u56fe\u50cf\u751f\u6210\u7684\u5f62\u6001\u53d1\u751f\u6a21\u578b\u3002\u4ed6\u4eec\u8bc1\u660e\u4e86\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc\u6765\u91cd\u5efa\u6574\u4e2a\u56fe\u50cf\u662f\u53ef\u80fd\u7684\uff0c\u5373\u4f7f\u6bcf\u4e2a\u5143\u80de\u5e76\u6ca1\u6709\u5173\u4e8e\u5176\u4f4d\u7f6e\u7684\u4fe1\u606f\uff0c\u53ea\u4f9d\u8d56\u6765\u81ea\u5176\u90bb\u5c45\u7684\u5c40\u90e8\u4fe1\u606f\u3002\u8fd9\u79cd\u65b9\u6cd5\u4f7f\u5f97\u751f\u6210\u7b97\u6cd5\u80fd\u591f\u62b5\u6297\u566a\u97f3\uff0c\u5e76\u5141\u8bb8\u56fe\u50cf\u5728\u53d7\u635f\u65f6\u518d\u751f\u3002\u795e\u7ecf\u5143\u80de\u81ea\u52a8\u673a\u7684\u4e00\u4e2a\u62d3\u5c55\u7248\u672c[50]\u4f7f\u5355\u4e2a\u5143\u80de\u80fd\u591f\u6267\u884c\u56fe\u50cf\u5206\u7c7b\u4efb\u52a1<\/span>\uff08\u5982MNIST\u6570\u5b57\u5206\u7c7b\uff09<\/span>\uff0c\u53ea\u901a\u8fc7\u68c0\u67e5\u5355\u4e2a\u50cf\u7d20\u7684\u5185\u5bb9\uff0c\u5e76\u5c06\u4fe1\u606f\u4f20\u9012\u7ed9\u8be5\u5143\u80de\u7684\u8fd1\u90bb<\/span>\uff08\u89c1\u56fe2\uff09<\/span>\u3002\u968f\u7740\u65f6\u95f4\u7684\u63a8\u79fb\uff0c\u8fd9\u4e9b\u5143\u80de\u5c06\u5f62\u6210\u5171\u8bc6\uff0c\u5373\u54ea\u4e2a\u6570\u5b57\u662f\u6700\u6709\u53ef\u80fd\u7684\u3002\u4f46\u6709\u8da3\u7684\u662f\uff0c\u5206\u6b67\u8fd8\u662f\u4f1a\u56e0\u4e3a\u50cf\u7d20\u4f4d\u7f6e\u800c\u4ea7\u751f\uff0c\u7279\u522b\u662f\u5728\u56fe\u50cf\u6545\u610f\u7cc5\u5408\u4e86\u4e0d\u540c\u6570\u5b57\u7684\u65f6\u5019\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u5229\u7528\u795e\u7ecf\u5143\u80de\u81ea\u52a8\u673a\u8fdb\u884c\u56fe\u50cf\u518d\u751f\u5e76\u4e0d\u5c40\u9650\u5728\u4e8c\u7ef4\u56fe\u50cf\u3002\u5728\u540e\u6765\u7684\u7814\u7a76\u4e2d\uff0cZhang\u7b49\u4eba[73]\u91c7\u7528\u4e86\u4e00\u79cd\u7c7b\u4f3c\u7684\u65b9\u6cd5\u6765\u751f\u6210\u4e09\u7ef4\u4f53\u7d20\u3002\u8fd9\u5bf9\u9ad8\u5206\u8fa8\u7387\u7684\u4e09\u7ef4\u626b\u63cf\u7279\u522b\u6709\u7528\uff0c\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u4e09\u7ef4\u5f62\u72b6\u7684\u6570\u636e\u5f80\u5f80\u7528\u7a00\u758f\u548c\u4e0d\u5b8c\u6574\u7684\u70b9\u6765\u63cf\u8ff0\u3002\u4f7f\u7528\u751f\u6210\u5f0f\u5143\u80de\u81ea\u52a8\u673a\uff0c\u4ed6\u4eec\u53ef\u4ee5\u4ece\u90e8\u5206\u70b9\u7684\u96c6\u5408\u4e2d\u6062\u590d\u5b8c\u6574\u7684\u4e09\u7ef4\u5f62\u72b6\u3002\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u4ec5\u5c40\u9650\u4e8e\u7eaf\u751f\u6210\u9886\u57df\uff0c\u4e5f\u53ef\u4ee5\u5e94\u7528\u4e8e\u6d3b\u8dc3\u73af\u5883<\/span>\uff08\u5982Minecraft\uff09<\/span>\u4e2d\u4eba\u5de5\u667a\u80fd\u4f53\u7684\u6784\u4ef6\u3002Sudhakaran\u7b49\u4eba[64]\u8bad\u7ec3\u795e\u7ecf\u5143\u80de\u81ea\u52a8\u673a\uff0c\u6765\u5728Minecraft\u4e2d\u751f\u957f\u590d\u6742\u7684\u5b9e\u4f53\uff0c\u5982\u57ce\u5821\u3001\u516c\u5bd3\u548c\u6811\uff0c\u6709\u4e9b\u5b9e\u4f53\u7531\u6210\u5343\u4e0a\u4e07\u7684\u5757\u6784\u6210\u3002\u9664\u4e86\u518d\u751f\uff0c\u5b83\u4eec\u7684\u7cfb\u7edf\u8fd8\u53ef\u4ee5\u4fee\u590d\u7b80\u5355\u529f\u80fd\u673a\u5668<\/span>\uff08\u5982\u6e38\u620f\u4e2d\u7684\u865a\u62df\u751f\u7269\uff09<\/span>\u7684\u90e8\u4ef6\u3002\u4ed6\u4eec\u6f14\u793a\u4e86\u4e00\u4e2a\u5f62\u6001\u53d1\u751f\u5b66\u7684\u751f\u7269\uff0c\u5728\u865a\u62df\u4e16\u754c\u4e2d\u88ab\u5207\u6210\u4e24\u534a\uff0c\u8fd8\u53ef\u4ee5\u751f\u957f\u6210\u4e24\u4e2a\u5206\u79bb\u7684\u751f\u7269<\/span>\uff08\u89c1\u56fe3\uff09<\/span>\u3002\u5143\u80de\u81ea\u52a8\u673a\u4e5f\u5929\u7136\u5730\u9002\u7528\u4e8e\u4e3a\u56fe\u50cf\u63d0\u4f9b\u89c6\u89c9\u89e3\u91ca\u3002Qin\u7b49\u4eba[45]\u7814\u7a76\u4e86\u5206\u5c42\u5143\u80de\u81ea\u52a8\u673a\u5728\u89c6\u89c9\u663e\u8457\u6027\u65b9\u9762\u7684\u5e94\u7528\uff0c\u5373\u8bc6\u522b\u56fe\u50cf\u4e2d\u7a81\u51fa\u7684\u90e8\u5206\u3002\u901a\u8fc7\u8ba9\u5143\u80de\u81ea\u52a8\u673a\u5bf9\u4ece\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u4e2d\u63d0\u53d6\u7684\u89c6\u89c9\u7279\u5f81\u8fdb\u884c\u64cd\u4f5c\uff0c\u4ed6\u4eec\u80fd\u591f\u8fed\u4ee3\u5730\u5efa\u6784\u56fe\u50cf\u7684\u591a\u5c3a\u5ea6\u663e\u8457\u6027\u56fe\uff0c\u4ece\u800c\u4f7f\u6700\u540e\u7684\u56fe\u50cf\u63a5\u8fd1\u76ee\u6807\u3002Sandler\u7b49\u4eba[56]\u540e\u6765\u7814\u7a76\u4e86\u5143\u80de\u81ea\u52a8\u673a\u5728\u56fe\u50cf\u5206\u5272\u4efb\u52a1\u4e0a\u7684\u5e94\u7528\uff0c\u8fd9\u662f\u4e00\u4e2a\u6df1\u5ea6\u5b66\u4e60\u5df2\u7ecf\u53d6\u5f97\u4e86\u5de8\u5927\u6210\u529f\u7684\u4efb\u52a1\u3002\u4ed6\u4eec\u8bc1\u660e\uff0c\u4f7f\u7528\u89c4\u5219\u76f8\u5bf9\u7b80\u5355\u7684\u5143\u80de\u81ea\u52a8\u673a<\/span>\uff08\u795e\u7ecf\u7f51\u7edc\u53c2\u6570\u53ea\u6709\u4e00\u4e07\uff09<\/span>\u6267\u884c\u590d\u6742\u7684\u5206\u5272\u4efb\u52a1\u662f\u53ef\u884c\u7684\u3002\u8be5\u65b9\u6cd5\u7684\u4f18\u70b9\u662f\u80fd\u591f\u6269\u5c55\u5230\u4ee4\u4eba\u96be\u4ee5\u7f6e\u4fe1\u7684\u5927\u5c3a\u5bf8\u4e0a\uff0c\u8fd9\u79cd\u62d3\u5c55\u5bf9\u53d7GPU\u5185\u5b58\u9650\u5236\u7684\u4f20\u7edf\u65b9\u6cd5\u662f\u4e00\u4e2a\u6311\u6218\u3002<\/span><\/section>\n
<\/span>
<\/section>\n
<\/section>\n
<\/span><\/section>\n
\u56fe3. \u795e\u7ecf\u5143\u80de\u81ea\u52a8\u673a\u4e5f\u88ab\u7528\u4e8eMinecraft\u6e38\u620f\u4e2d\u5b9e\u4f53\u7684\u518d\u751f\u3002Sudhakaran\u7b49\u4eba\u7684\u6784\u9020\u4e0d\u4ec5\u4f7fMinecraft\u5efa\u7b51\u3001\u6811\u6728\u80fd\u591f\u518d\u751f\uff0c\u800c\u4e14\u4f7f\u5f97\u6e38\u620f\u4e2d\u7684\u7b80\u5355\u529f\u80fd\u673a\u5668\uff0c\u5982\u8815\u866b\u72b6\u751f\u7269\u5728\u88ab\u5207\u65ad\u65f6\uff0c\u80fd\u591f\u518d\u751f\u6210\u4e24\u4e2a\u5206\u79bb\u7684\u751f\u7269\u3002<\/span><\/section>\n
 <\/span><\/section>\n

\n
2\u3001\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60<\/span><\/strong><\/span><\/section>\n

<\/span><\/section>\n<\/h4>\n
\u4f7f\u7528\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u8fdb\u884c\u5f3a\u5316\u5b66\u4e60\uff0c\u5373\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60<\/span>\uff08deep reinforcement learning, Deep RL\uff09<\/span>\uff0c\u4e0e\u6df1\u5ea6\u5b66\u4e60\u7684\u5174\u8d77\u662f\u540c\u6b65\u7684\u3002\u6df1\u5ea6\u5b66\u4e60\u4e3a\u5f3a\u5316\u5b66\u4e60\u667a\u80fd\u4f53\u914d\u5907\u4e86\u73b0\u4ee3\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\uff0c\u53ef\u4ee5\u89e3\u51b3\u66f4\u590d\u6742\u7684\u95ee\u9898\uff0c\u5982\u9ad8\u7ef4\u8fde\u7eed\u63a7\u5236\u6216\u57fa\u4e8e\u50cf\u7d20\u7ea7\u89c2\u6d4b\u7684\u89c6\u89c9\u4efb\u52a1\u3002\u867d\u7136\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u4e0e\u6df1\u5ea6\u5b66\u4e60\u6709\u540c\u6837\u7684\u4f18\u70b9\uff0c\u5373\u8ba1\u7b97\u8d44\u6e90\u8db3\u591f\uff0c\u4e00\u822c\u5c31\u80fd\u53d1\u73b0\u76ee\u6807\u4efb\u52a1\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u4f46\u524d\u8005\u6709\u7740\u4e0e\u540e\u8005\u4e00\u6837\u7684\u5c40\u9650\u6027\u3002\u5f53\u4efb\u52a1\u7a0d\u6709\u6539\u53d8\u65f6\uff0c\u4e3a\u6267\u884c\u67d0\u4e00\u7279\u5b9a\u4efb\u52a1\u800c\u8bad\u7ec3\u7684\u667a\u80fd\u4f53\u5f80\u5f80\u4f1a\u5931\u8d25\u3002\u6b64\u5916\uff0c\u795e\u7ecf\u7f51\u7edc\u7684\u89e3\u51b3\u65b9\u6848\u4e00\u822c\u53ea\u5728\u6709\u660e\u786e\u7684\u8f93\u5165-\u8f93\u51fa\u6620\u5c04\u3001\u9488\u5bf9\u7279\u5b9a\u7684\u5f62\u6001\u65f6\u9002\u7528\u3002\u4f8b\u5982\uff0c\u4e3a\u56db\u6761\u817f\u7684\u8682\u8681\u8bad\u7ec3\u7684\u8fd0\u52a8\u7b56\u7565\uff0c\u53ef\u80fd\u5bf9\u516d\u6761\u817f\u7684\u8682\u8681\u4e0d\u8d77\u4f5c\u7528\u3002\u5982\u679c\u4e00\u4e2a\u667a\u80fd\u4f53\u88ab\u8bbe\u8ba1\u6210\u63a5\u53d710\u4e2a\u8f93\u5165\uff0c\u800c\u4f60\u7ed9\u5b83\u8f93\u5165\u4e865\u4e2a\u6216\u800520\u4e2a\uff0c\u5b83\u5c31\u65e0\u6cd5\u5de5\u4f5c\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6f14\u5316\u8ba1\u7b97\u754c\u5f88\u65e9\u5c31\u5f00\u59cb\u5904\u7406\u4e0a\u8ff0\u7684\u4e00\u4e9b\u6311\u6218\uff0c\u5c06\u6a21\u5757\u5316<\/strong><\/span>\uff08modularity\uff09<\/span>\u7eb3\u5165\u51b3\u5b9a\u4e86\u4eba\u5de5\u667a\u80fd\u4f53\u8bbe\u8ba1\u7684\u6f14\u5316\u8fc7\u7a0b\u4e2d\u3002\u667a\u80fd\u4f53\u7531\u76f8\u540c\u4f46\u72ec\u7acb\u7684\u6a21\u5757\u7ec4\u6210\u3002\u6a21\u5757\u4e4b\u95f4\u7684\u5c40\u90e8\u4e92\u52a8\u4fc3\u8fdb\u81ea\u7ec4\u7ec7\uff0c\u4f7f\u7cfb\u7edf\u5bf9\u5f62\u6001\u5b66\u7684\u53d8\u5316\u5177\u6709\u7a33\u5065\u6027<\/strong>\u3002\u5bf9\u6f14\u5316\u800c\u6765\u7684\u7cfb\u7edf\u6765\u8bf4\uff0c\u62e5\u6709\u8fd9\u79cd\u6027\u8d28\u662f\u4e00\u4e2a\u57fa\u672c\u8981\u6c42\u3002\u8fd9\u4e9b\u89c2\u5ff5\u5df2\u7ecf\u51fa\u73b0\u5728\u5173\u4e8e\u8f6f\u4f53\u673a\u5668\u4eba\u7684\u6587\u732e\u91cc[8]\uff0c\u6587\u4e2d\u62a5\u544a\u7684\u673a\u5668\u4eba\u7531\u7f51\u683c\u5316\u7684\u4f53\u7d20\u7ec6\u80de\u7ec4\u6210\uff0c\u6bcf\u4e2a\u7ec6\u80de\u7531\u72ec\u7acb\u7684\u795e\u7ecf\u7f51\u7edc\u63a7\u5236\uff0c\u5177\u6709\u5c40\u90e8\u611f\u77e5\u529f\u80fd\uff0c\u53ef\u4ee5\u4ea7\u751f\u5c40\u90e8\u7684\u884c\u52a8\u3002\u901a\u8fc7\u4fe1\u606f\u4f20\u9012\uff0c\u7ec4\u6210\u8fd9\u4e00\u673a\u5668\u4eba\u7684\u7ec6\u80de\u7fa4\u80fd\u591f\u81ea\u7ec4\u7ec7\uff0c\u5e76\u6267\u884c\u4e00\u7cfb\u5217\u7684\u8fd0\u52a8\u4efb\u52a1<\/span>\uff08\u89c1\u56fe4\uff09<\/span>\u3002\u540e\u6765\u7684\u7814\u7a76[31]\u751a\u81f3\u63d0\u51fa\uff0c\u53ef\u4ee5\u5728\u7ec6\u80de\u5e03\u7f6e\u7684\u6f14\u5316\u4e2d\u52a0\u5165\u53d8\u5f62\uff0c\u4ee5\u4ea7\u751f\u5728\u4e00\u7cfb\u5217\u73af\u5883\u4e2d\u90fd\u80fd\u7a33\u5065\u7684\u914d\u7f6e\u3002\u6700\u8fd1\uff0c\u8f6f\u4f53\u673a\u5668\u4eba\u751a\u81f3\u7ed3\u5408\u4e86\u524d\u9762\u8ba8\u8bba\u7684\u795e\u7ecf\u5143\u80de\u81ea\u52a8\u673a\uff0c\u4f7f\u8fd9\u4e9b\u673a\u5668\u4eba\u80fd\u591f\u81ea\u6211\u518d\u751f[28]\u3002\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u754c\u91cc\u5e38\u7528\u7eaf\u7b56\u7565\u4f18\u5316\uff0c\u800c\u8f6f\u4f53\u673a\u5668\u4eba\u6587\u732e\u91cc\u5e38\u89c1\u5173\u4e8e\u201c\u8f6f\u4f53-\u7b56\u7565\u534f\u540c\u8fdb\u5316\u201d\u7684\u7814\u7a76\uff0c\u4e3a\u4e86\u8fde\u63a5\u8fd9\u4e24\u8005\uff0cBhatia\u7b49\u4eba[3]\u6700\u8fd1\u5f00\u53d1\u4e86\u4e00\u4e2a\u7c7b\u4f3c\u4e8eOpenAI Gym\u7684\u73af\u5883\uff0c\u79f0\u4e3aEvolution Gym\u3002\u8fd9\u662f\u4e00\u4e2a\u57fa\u51c6\u5e73\u53f0\uff0c\u80fd\u5f00\u53d1\u548c\u6bd4\u8f83\u4e00\u4e9b\u80fd\u5bf9\u8bbe\u8ba1\u4e0e\u63a7\u5236\u8fdb\u884c\u534f\u540c\u4f18\u5316\u7684\u7b97\u6cd5\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7528C++\u7f16\u5199\u7684\u9ad8\u6548\u7684\u8f6f\u4f53\u673a\u5668\u4eba\u6a21\u62df\u5668\uff0c\u5e76\u5e26\u6709Python\u63a5\u53e3\u3002<\/span><\/section>\n

<\/section>\n
<\/section>\n

\u56fe4. \u5728\u4e8c\u7ef4\u548c\u4e09\u7ef4\u7a7a\u95f4\u91cc\u6a21\u62df\u8f6f\u4f53\u673a\u5668\u4eba\u7684\u4f8b\u5b50\u3002\u6bcf\u4e2a\u7ec6\u80de\u4ee3\u8868\u4e00\u4e2a\u72ec\u7acb\u7684\u795e\u7ecf\u7f51\u7edc\uff0c\u5177\u6709\u5c40\u90e8\u611f\u77e5\u529f\u80fd\uff0c\u80fd\u4ea7\u751f\u5c40\u90e8\u7684\u52a8\u4f5c\uff0c\u5305\u62ec\u4e0e\u76f8\u90bb\u7ec6\u80de\u8fdb\u884c\u4ea4\u6d41\u3002\u8bad\u7ec3\u8fd9\u4e9b\u7cfb\u7edf\u6765\u5b8c\u6210\u5404\u79cd\u4efb\u52a1\uff0c\u4e0d\u4ec5\u6d89\u53ca\u5230\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc\uff0c\u8fd8\u6d89\u53ca\u5230\u5bf9\u5f62\u6210\u667a\u80fd\u4f53\u5f62\u6001\u7684\u8f6f\u4f53\u7ec6\u80de\u7684\u8bbe\u8ba1\u548c\u5e03\u7f6e\u3002\u56fe\u7247\u6765\u81eaHoribe\u7b49\u4eba\u7684\u7814\u7a76[28]\u3002<\/span><\/p>\n

 <\/span><\/section>\n
\u6a21\u5757\u5316\u7684\u3001\u5206\u6563\u7684\u81ea\u7ec4\u7ec7\u63a7\u5236\u5668\uff0c\u5728\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u754c\u4e5f\u6709\u4eba\u5728\u63a2\u7d22\u3002Wang\u7b49\u4eba[69]\u548cHuang\u7b49\u4eba[29]\u63a2\u7d22\u4e86\u4f7f\u7528\u6a21\u5757\u795e\u7ecf\u7f51\u7edc<\/strong>\u6765\u63a7\u5236\u4e00\u4e2a\u6a21\u62df\u673a\u5668\u4eba\u7684\u5404\u4e2a\u4f20\u52a8\u5668\u6765\u5b9e\u73b0\u8fde\u7eed\u63a7\u5236\u3002\u4ed6\u4eec\u5c06\u5168\u5c40\u8fd0\u52a8\u7b56\u7565\u89c6\u4e3a\u6a21\u5757\u795e\u7ecf\u7f51\u7edc<\/span>\uff08\u5728Huang\u7b49\u4eba\u7684\u4f8b\u5b50[29]\u91cc\u662f\u76f8\u540c\u7684\u795e\u7ecf\u7f51\u7edc\uff09<\/span>\u7684\u96c6\u5408\uff0c\u5bf9\u5e94\u667a\u80fd\u4f53\u7684\u5404\u4e2a\u4f20\u52a8\u5668\uff0c\u5e76\u4f7f\u7528\u5f3a\u5316\u5b66\u4e60\u6765\u8bad\u7ec3\u7cfb\u7edf\u3002\u50cf\u8f6f\u4f53\u673a\u5668\u4eba\u4e00\u6837\uff0c\u6bcf\u4e2a\u6a21\u5757\u53ea\u8d1f\u8d23\u63a7\u5236\u5176\u76f8\u5e94\u7684\u4f20\u52a8\u5668\uff0c\u5e76\u4e14\u53ea\u4ece\u5c40\u90e8\u4f20\u611f\u5668\u63a5\u53d7\u4fe1\u606f<\/span>\uff08\u89c1\u56fe5\uff09<\/span>\u3002\u6d88\u606f\u5728\u76f8\u90bb\u6a21\u5757\u4e4b\u95f4\u4f20\u9012\uff0c\u9010\u6e10\u4f20\u64ad\u5230\u9065\u8fdc\u7684\u6a21\u5757\u3002\u4ed6\u4eec\u8868\u660e\uff0c\u4e00\u4e2a\u5355\u4e00\u7684\u6a21\u5757\u7b56\u7565\u53ef\u4ee5\u4e3a\u51e0\u79cd\u4e0d\u540c\u5f62\u6001\u7684\u673a\u5668\u4eba\u4ea7\u751f\u8fd0\u52a8\u884c\u4e3a\uff0c\u800c\u4e14\u8fd9\u4e9b\u7b56\u7565\u53ef\u4ee5\u6cdb\u5316\u5230\u8bad\u7ec3\u4e2d\u672a\u89c1\u7684\u5f62\u6001\uff0c\u6bd4\u5982\u6709\u989d\u5916\u7684\u817f\u7684\u751f\u7269\u3002\u4e0e\u8f6f\u4f53\u673a\u5668\u4eba\u7684\u60c5\u51b5\u4e00\u6837\uff0c\u8fd9\u4e9b\u7ed3\u679c\u4e5f\u8bc1\u660e\uff0c\u5206\u6563\u6a21\u5757\u4e4b\u95f4\u7684\u4fe1\u606f\u4f20\u9012\u4e2d\u53ef\u4ee5\u6d8c\u73b0\u51fa\u4e2d\u5fc3\u5316\u7684\u534f\u4f5c\uff0c\u534f\u540c\u5730\u4f18\u5316\u4e00\u4e2a\u5171\u4eab\u7684\u5956\u52b1\u3002<\/span><\/section>\n
 <\/span><\/section>\n

<\/p>\n

\u56fe5. \u5bf9\u7279\u5b9a\u5177\u6709\u56fa\u5b9a\u5f62\u6001\u7684\u673a\u5668\u4eba\uff0c\u4f20\u7edf\u5f3a\u5316\u5b66\u4e60\u65b9\u6cd5\u8bad\u7ec3\u7684\u662f\u4e00\u4e2a\u7279\u5b9a\u7684\u7b56\u7565\u3002\u4f46\u6700\u8fd1\u7684\u5de5\u4f5c\uff0c\u6bd4\u5982\u672c\u56fe\u5c55\u73b0\u7684Huang\u7b49\u4eba\u7684\u7814\u7a76[29]\uff0c\u8bd5\u56fe\u8bad\u7ec3\u4e00\u4e2a\u5355\u4e00\u7684\u6a21\u5757\u795e\u7ecf\u7f51\u7edc\uff0c\u8d1f\u8d23\u63a7\u5236\u673a\u5668\u4eba\u7684\u4e00\u4e2a\u90e8\u5206\u3002\u56e0\u6b64\uff0c\u6bcf\u4e2a\u673a\u5668\u4eba\u7684\u5168\u5c40\u7b56\u7565\u662f\u8fd9\u4e9b\u76f8\u540c\u7684\u6a21\u5757\u5316\u795e\u7ecf\u7f51\u7edc\u534f\u8c03\u7684\u7ed3\u679c\u3002\u4ed6\u4eec\u8868\u660e\uff0c\u8fd9\u6837\u7684\u7cfb\u7edf\u53ef\u4ee5\u5728\u5404\u79cd\u4e0d\u540c\u7684\u9aa8\u67b6\u7ed3\u6784\u4e2d\u901a\u7528\uff0c\u4ece\u8df3\u866b\u5230\u56db\u8db3\u6b65\u884c\u7c7b\uff0c\u751a\u81f3\u662f\u4e00\u4e9b\u672a\u89c1\u8fc7\u7684\u5f62\u6001\u3002<\/span><\/p>\n


<\/section>\n
\u4e0a\u8ff0\u7814\u7a76\u6697\u793a\u4e86\u5177\u8eab\u8ba4\u77e5<\/strong>\u7684\u529b\u91cf\u3002\u5177\u8eab\u8ba4\u77e5\u5f3a\u8c03\u4e86\u667a\u80fd\u4f53\u7684\u8eab\u4f53\u5728\u4ea7\u751f\u884c\u4e3a\u8fc7\u7a0b\u4e2d\u7684\u4f5c\u7528\u3002\u867d\u7136\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u7684\u5927\u90e8\u5206\u7814\u7a76\u91cd\u70b9\uff0c\u662f\u4e3a\u5177\u6709\u56fa\u5b9a\u8bbe\u8ba1\u7684\u667a\u80fd\u4f53<\/span>\uff08\u5982\u53cc\u8db3\u673a\u5668\u4eba\u3001\u4eba\u5f62\u673a\u5668\u4eba\u6216\u673a\u68b0\u81c2\uff09<\/span>\u8bbe\u8ba1\u795e\u7ecf\u7f51\u7edc\u7b56\u7565\uff0c\u4f46\u5177\u8eab\u667a\u80fd\u5728\u8be5\u9886\u57df\u91cc\u4e5f\u5728\u9010\u6e10\u5438\u5f15\u5174\u8da3[22,44]\u3002\u53d7\u4ee5\u524d\u81ea\u914d\u7f6e\u6a21\u5757\u5316\u673a\u5668\u4eba\u7684\u7814\u7a76[61]\u7684\u542f\u53d1\uff0cPathak\u7b49\u4eba[44]\u7814\u7a76\u4e86\u4e00\u4e2a\u539f\u59cb\u667a\u80fd\u4f53\u7684\u96c6\u5408\uff0c\u8fd9\u4e9b\u667a\u80fd\u4f53\u5b66\u7740\u81ea\u7ec4\u88c5\u4e00\u4e2a\u590d\u6742\u7684\u8eab\u4f53\uff0c\u5e76\u5b66\u4e60\u5728\u6ca1\u6709\u660e\u786e\u7684\u4e2d\u5fc3\u5316\u63a7\u5236\u5355\u5143\u7684\u60c5\u51b5\u4e0b\uff0c\u5229\u7528\u5c40\u90e8\u7b56\u7565\u6765\u63a7\u5236\u8eab\u4f53<\/span>\uff08\u89c1\u56fe6\uff09<\/span>\u3002\u6bcf\u4e2a\u539f\u59cb\u667a\u80fd\u4f53<\/span>\uff08\u7531\u4e00\u4e2a\u80a2\u4f53\u548c\u4e00\u4e2a\u9a6c\u8fbe\u7ec4\u6210\uff09<\/span>\u53ef\u4ee5\u8fde\u63a5\u9644\u8fd1\u7684\u667a\u80fd\u4f53\uff0c\u8fd9\u6837\u4e00\u6765\uff0c\u590d\u6742\u7684\u5f62\u6001\u5c31\u53ef\u80fd\u6d8c\u73b0\u3002\u4ed6\u4eec\u7684\u7814\u7a76\u7ed3\u679c\u8868\u660e\uff0c\u8fd9\u4e9b\u52a8\u6001\u3001\u6a21\u5757\u5316\u7684\u667a\u80fd\u4f53\uff0c\u5bf9\u6761\u4ef6\u7684\u53d8\u5316\u662f\u7a33\u5065\u7684\u3002\u7b56\u7565\u4e0d\u4ec5\u53ef\u4ee5\u6cdb\u5316\u5230\u672a\u89c1\u8fc7\u7684\u73af\u5883\uff0c\u8fd8\u53ef\u4ee5\u6cdb\u5316\u5230\u7531\u66f4\u591a\u6a21\u5757\u7ec4\u6210\u7684\u3001\u672a\u89c1\u8fc7\u7684\u5f62\u6001\u3002\u9664\u4e86\u9002\u5e94\u4e0d\u65ad\u53d8\u5316\u7684\u5f62\u6001\u4e0e\u73af\u5883\uff0c\u81ea\u7ec4\u7ec7\u7cfb\u7edf\u8fd8\u80fd\u9002\u5e94\u5176\u611f\u5b98\u8f93\u5165\u7684\u53d8\u5316\u3002\u611f\u5b98\u66ff\u4ee3\u6307\u7684\u662f\u5927\u8111\u4f7f\u7528\u4e00\u79cd\u611f\u5b98\u6a21\u6001<\/span>\uff08\u5982\u89e6\u89c9\uff09<\/span>\u6765\u63d0\u4f9b\u901a\u5e38\u7531\u53e6\u4e00\u79cd\u6a21\u6001<\/span>\uff08\u5982\u89c6\u89c9\uff09<\/span>\u6536\u96c6\u7684\u73af\u5883\u4fe1\u606f\u7684\u80fd\u529b\u3002\u7136\u800c\uff0c\u5927\u591a\u6570\u795e\u7ecf\u7f51\u7edc\u5e76\u4e0d\u80fd\u9002\u5e94\u611f\u5b98\u66ff\u4ee3\u3002\u4f8b\u5982\uff0c\u5927\u591a\u6570\u5f3a\u5316\u5b66\u4e60\u667a\u80fd\u4f53\u8981\u6c42\u8f93\u5165\u5fc5\u987b\u7b26\u5408\u7cbe\u786e\u7684\u3001\u5b9e\u73b0\u6307\u5b9a\u7684\u56fa\u5b9a\u683c\u5f0f\uff0c\u5426\u5219\u5c31\u4f1a\u5931\u6548\u3002\u5728\u6700\u8fd1\u7684\u4e00\u9879\u7814\u7a76\u4e2d\uff0cTang\u548cHa[65]\u63a2\u8ba8\u4e86\u53ef\u4ee5\u4e0d\u53d7\u8f93\u5165\u6253\u4e71\u5f71\u54cd\u7684\u795e\u7ecf\u7f51\u7edc\u667a\u80fd\u4f53\uff0c\u8981\u6c42\u6bcf\u4e2a\u611f\u89c9\u795e\u7ecf\u5143<\/span>\uff08\u4ece\u73af\u5883\u4e2d\u63a5\u53d7\u611f\u5b98\u8f93\u5165\u7684\u53d7\u4f53\uff09<\/span>\u63a8\u65ad\u5176\u8f93\u5165\u4fe1\u53f7\u7684\u610f\u4e49\u548c\u80cc\u666f\uff0c\u800c\u4e0d\u662f\u660e\u786e\u5730\u5047\u8bbe\u4e00\u4e2a\u56fa\u5b9a\u7684\u610f\u4e49<\/span>\uff08\u89c1\u56fe7\uff09<\/span>\u3002\u4ed6\u4eec\u8bc1\u660e\uff0c\u8fd9\u4e9b\u611f\u89c9\u7f51\u7edc\u53ef\u4ee5\u88ab\u8bad\u7ec3\uff0c\u6765\u6574\u5408\u5c40\u90e8\u6536\u5230\u7684\u4fe1\u606f\uff0c\u5e76\u4e14\u53ef\u4ee5\u901a\u8fc7\u795e\u7ecf\u5143\u4e4b\u95f4\u4f7f\u7528\u6ce8\u610f\u529b\u673a\u5236\u7684\u4ea4\u6d41\uff0c\u6765\u534f\u540c\u4ea7\u751f\u4e00\u4e2a\u5168\u5c40\u4e00\u81f4\u7684\u7b56\u7565\u3002\u6b64\u5916\uff0c\u5373\u4f7f\u5728\u4e00\u6bb5\u65f6\u95f4\u91cc\uff0c\u8be5\u7cfb\u7edf\u7684\u8f93\u5165\u987a\u5e8f\u88ab\u968f\u673a\u6539\u53d8\u51e0\u6b21\uff0c\u5b83\u4ecd\u7136\u53ef\u4ee5\u6267\u884c\u4efb\u52a1\u3002\u4ed6\u4eec\u7684\u5b9e\u9a8c\u8868\u660e\uff0c\u8fd9\u79cd\u667a\u80fd\u4f53\u5bf9\u5305\u542b\u8bb8\u591a\u5197\u4f59\u4fe1\u606f\u6216\u566a\u58f0\u7684\u89c2\u6d4b\uff0c\u6216\u8005\u5bf9\u635f\u574f\u6216\u4e0d\u5b8c\u6574\u7684\u89c2\u6d4b\uff0c\u90fd\u5177\u6709\u7a33\u5065\u6027\u3002<\/span><\/section>\n
 <\/span><\/section>\n
<\/section>\n

\u56fe6. \u81ea\u7ec4\u7ec7\u4e5f\u4f7f\u5f97\u5f3a\u5316\u5b66\u4e60\u8bad\u7ec3\u73af\u5883\u4e2d\u7684\u7cfb\u7edf\u80fd\u591f\u5728\u7ed9\u5b9a\u4efb\u52a1\u65f6\u8fdb\u884c\u81ea\u914d\u7f6e\uff08\u81ea\u8bbe\u8ba1\uff09\u3002Pathak\u7b49\u4eba[44]\u63a2\u8ba8\u4e86\u8fd9\u79cd\u52a8\u6001\u548c\u6a21\u5757\u5316\u7684\u667a\u80fd\u4f53\uff0c\u5e76\u6807\u660e\u5b83\u4eec\u4e0d\u4ec5\u53ef\u4ee5\u6cdb\u5316\u5230\u672a\u89c1\u8fc7\u7684\u73af\u5883\uff0c\u8fd8\u53ef\u4ee5\u6cdb\u5316\u5230\u7531\u989d\u5916\u6a21\u5757\u7ec4\u6210\u7684\u672a\u89c1\u8fc7\u7684\u5f62\u6001\u3002<\/span><\/p>\n


<\/section>\n
<\/section>\n

\u56fe7. Tang\u548cHa[65]\u63a2\u8ba8\u4e86\u5229\u7528\u4e86\u81ea\u7ec4\u7ec7\u548c\u6ce8\u610f\u529b\u7279\u6027\u7684\u5f3a\u5316\u5b66\u4e60\u667a\u80fd\u4f53\uff0c\u8fd9\u79cd\u667a\u80fd\u4f53\u5c06\u5b83\u4eec\u7684\u89c2\u6d4b\u89c6\u4e3a\u4e00\u4e2a\u5305\u542b\u4e86\u611f\u5b98\u8f93\u5165\u7684\uff0c\u4efb\u610f\u6392\u5e8f\u7684\u3001\u957f\u5ea6\u53ef\u53d8\u7684\u5217\u8868\u3002\u4ed6\u4eec\u5c06\u89c6\u89c9\u4efb\u52a1\uff08\u5982CarRacing\u4f55Atari Pong[4,66]\uff09\u4e2d\u7684\u8f93\u5165\u5212\u5206\u4e3a\u4e00\u4e2a\u4e8c\u7ef4\u7f51\u683c\uff0c\u5e76\u6253\u4e71\u4e86\u987a\u5e8f\uff08\u5de6\u56fe\uff09\u3002\u4ed6\u4eec\u8fd8\u5728\u8fde\u7eed\u63a7\u5236\u4efb\u52a1[18]\u4e2d\uff0c\u4ee5\u4e71\u5e8f\u589e\u52a0\u4e86\u8bb8\u591a\u989d\u5916\u7684\u566a\u97f3\u8f93\u5165\u901a\u9053\uff08\u53f3\u56fe\uff09\uff1b\u667a\u80fd\u4f53\u5fc5\u987b\u5b66\u4f1a\u8bc6\u522b\u54ea\u4e9b\u8f93\u5165\u662f\u6709\u7528\u7684\u3002\u7cfb\u7edf\u4e2d\u7684\u6bcf\u4e2a\u611f\u89c9\u795e\u7ecf\u5143\u90fd\u6536\u5230\u5404\u81ea\u7684\u8f93\u5165\u6d41\uff0c\u5e76\u901a\u8fc7\u534f\u8c03\u6765\u5b8c\u6210\u624b\u5934\u7684\u4efb\u52a1\u3002<\/span><\/p>\n

 <\/span>
<\/section>\n

\n
3\u3001\u591a\u667a\u80fd\u4f53\u5b66\u4e60<\/span><\/strong><\/span><\/section>\n<\/h4>\n

<\/section>\n
\u96c6\u4f53\u667a\u80fd\u53ef\u4ee5\u4ece\u51e0\u4e2a\u4e0d\u540c\u7684\u5c3a\u5ea6\u6765\u770b\u5f85\u3002\u52a8\u7269\u4e2a\u4f53\u53ef\u4ee5\u88ab\u770b\u6210\u662f\u534f\u540c\u5de5\u4f5c\u7684\u5668\u5b98\u7684\u96c6\u5408\uff0c\u800c\u6bcf\u4e2a\u5668\u5b98<\/span>\uff08\u5305\u62ec\u5927\u8111\uff09<\/span>\u53ef\u4ee5\u88ab\u770b\u6210\u662f\u534f\u540c\u8fd0\u4f5c\u7684\u7ec6\u80de\u7684\u96c6\u5408\u3002\u5728\u4e0a\u4e00\u8282\u4e2d\uff0c\u6211\u4eec\u8ba8\u8bba\u4e86\u51e0\u9879\u7814\u7a76\uff0c\u5b83\u4eec\u5229\u7528\u96c6\u4f53\u667a\u6167\u7684\u529b\u91cf\uff0c\u5c06\u4e00\u4e2a\u5355\u4e00\u7684\u5f3a\u5316\u5b66\u4e60\u667a\u80fd\u4f53\u4ece\u6839\u672c\u4e0a\u5206\u89e3\u6210\u8f83\u5c0f\u7684\u5f3a\u5316\u5b66\u4e60\u667a\u80fd\u4f53\u7684\u4e00\u4e2a\u96c6\u5408\uff0c\u534f\u540c\u4e3a\u4e00\u4e2a\u7fa4\u4f53\u76ee\u6807\u5de5\u4f5c\u3002\u4f46\u8fdb\u4e00\u6b65\u653e\u5927\u65f6\uff0c\u6211\u4eec\u4e5f\u53ef\u4ee5\u8d85\u8d8a\u751f\u7269\u5b66\u6765\u770b\u5f85\u4eba\u7c7b\u7684\u667a\u6167\uff0c\u628a\u4eba\u7c7b\u6587\u660e\u5f53\u505a\u662f\u89e3\u51b3\u8d85\u8fc7\u5355\u4e2a\u4eba\u80fd\u529b\u7684\u96c6\u4f53\u667a\u6167\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u591a\u667a\u80fd\u4f53\u95ee\u9898\u89c6\u4e3a\u793e\u4f1a\u5c42\u9762\u7684\u96c6\u4f53\u667a\u80fd\u6a21\u578b\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u867d\u7136\u591a\u667a\u80fd\u4f53\u5f3a\u5316\u5b66\u4e60<\/strong><\/span>\uff08multi-agent reinforcement learning, MARL\uff09<\/span>\u662f\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u4e00\u4e2a\u6210\u719f\u7684\u5206\u652f\uff0c\u4f46\u63d0\u51fa\u7684\u5927\u90e8\u5206\u5b66\u4e60\u7b97\u6cd5\u548c\u73af\u5883\uff0c\u9488\u5bf9\u7684\u90fd\u662f\u76f8\u5bf9\u8f83\u5c11\u7684\u667a\u80fd\u4f53[17,41]\u2014\u2014\u901a\u5e38\u5c11\u4e8e\u51e0\u5341\u4e2a[1,30,52,67]\u3002\u5728\u7ade\u4e89\u6027\u3001\u81ea\u535a\u5f08\u7684\u7814\u7a76\u4e2d\uff0c2\u4e2a\u667a\u80fd\u4f53\u548c4\u4e2a\u667a\u80fd\u4f53\u7684\u73af\u5883\u683c\u5916\u5e38\u89c1[2,23,36]\u3002\u7136\u800c\uff0c\u5728\u81ea\u7136\u754c\u4e2d\u89c2\u5bdf\u5230\u7684\u96c6\u4f53\u667a\u6167<\/span>\uff08\u6d89\u53ca\u6570\u5343\u5230\u6570\u767e\u4e07\u7684\u65cf\u7fa4\u89c4\u6a21\uff09<\/span>\uff0c\u4f9d\u8d56\u7684\u4e2a\u4f53\u6570\u91cf\u8fdc\u8fdc\u5927\u4e8e\u591a\u667a\u80fd\u4f53\u5f3a\u5316\u5b66\u4e60\u901a\u5e38\u4f1a\u7814\u7a76\u7684\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u7684\u6700\u65b0\u8fdb\u5c55\u5df2\u7ecf\u8bc1\u660e\uff0c\u5728\u590d\u6742\u76843D\u6a21\u62df\u73af\u5883\u4e2d\uff0c\u4ec5\u7528\u4e00\u4e2aGPU\uff0c\u5c31\u80fd\u6a21\u62df\u6210\u5343\u4e0a\u4e07\u7684\u667a\u80fd\u4f53[25,53]\u3002\u4e00\u4e2a\u91cd\u8981\u7684\u6311\u6218\u662f\uff1a\u5982\u4f55\u5229\u7528\u5e76\u884c\u8ba1\u7b97\u786c\u4ef6\u548c\u5206\u5e03\u5f0f\u8ba1\u7b97\u65b9\u9762\u7684\u8fdb\u5c55\uff0c\u5728\u66f4\u5927\u89c4\u6a21\u4e0a\u5904\u7406\u591a\u667a\u80fd\u4f53\u5b66\u4e60\uff0c\u6765\u8fbe\u5230\u8bad\u7ec3\u6570\u767e\u4e07\u667a\u80fd\u4f53\u7684\u76ee\u7684\u3002\u5728\u672c\u8282\u4e2d\uff0c\u6211\u4eec\u5c06\u4e3e\u4f8b\u8bf4\u660e\u8fd1\u671f\u5b66\u672f\u754c\u5728\u8bad\u7ec3\u5927\u91cf\u5728\u7fa4\u4f53\u73af\u5883\u4e2d\u4e92\u52a8\u7684\u667a\u80fd\u4f53\u65b9\u9762\u6240\u505a\u7684\u5c1d\u8bd5\u3002<\/span><\/section>\n
 <\/span><\/section>\n
Zhang\u7b49\u4eba[74]\u5f00\u53d1\u4e86\u4e00\u4e2a\u540d\u4e3aMAgent\u7684\u5e73\u53f0\uff0c\u8fd9\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u7f51\u683c\u4e16\u754c\u73af\u5883\uff0c\u53ef\u4ee5\u5141\u8bb8\u6570\u767e\u4e07\u7684\u795e\u7ecf\u7f51\u7edc\u667a\u80fd\u4f53\u3002\u4ed6\u4eec\u7684\u91cd\u70b9\u662f\u53ef\u62d3\u5c55\u6027\uff0c\u800c\u4e0d\u662f\u5173\u6ce8\u7269\u7406\u7684\u903c\u771f\u5ea6\u6216\u8005\u73af\u5883\u7684\u771f\u5b9e\u6027\u3002\u4ed6\u4eec\u8bc1\u660e\uff0cMAgent\u53ef\u4ee5\u5728\u4e00\u4e2aGPU\u4e0a\u627f\u8f7d\u591a\u8fbe\u4e00\u767e\u4e07\u7684\u667a\u80fd\u4f53<\/span>\uff082017\u5e74\uff09<\/span>\u3002\u4ed6\u4eec\u7684\u5e73\u53f0\u652f\u6301\u667a\u80fd\u4f53\u7fa4\u4f53\u5185\u90e8\u7684\u4e92\u52a8\uff0c\u8fd9\u4e0d\u4ec5\u6709\u5229\u4e8e\u7814\u7a76\u7b56\u7565\u4f18\u5316\u7684\u5b66\u4e60\u7b97\u6cd5\uff0c\u66f4\u5173\u952e\u7684\u662f\uff0c\u80fd\u591f\u7814\u7a76\u4eba\u5de5\u667a\u80fd\u793e\u4f1a\u4e2d\u6570\u767e\u4e07\u667a\u80fd\u4f53\u6d8c\u73b0\u7684\u793e\u4f1a\u73b0\u8c61\uff0c\u5305\u62ec\u901a\u4fe1\u8bed\u8a00\u548c\u793e\u4f1a\u7b49\u7ea7\u7ed3\u6784<\/strong>\u3002\u73af\u5883\u53ef\u4ee5\u901a\u8fc7\u811a\u672c\u5efa\u7acb\uff0c\u4ed6\u4eec\u5df2\u7ecf\u63d0\u4f9b\u4e86\u4e00\u4e9b\u6a21\u62df\u7684\u4f8b\u5b50\uff0c\u5982\u6355\u98df\u8005-\u730e\u7269\u3001\u6218\u573a\u3001\u5bf9\u6297\u6027\u8ffd\u51fb\uff0c\u652f\u6301\u80fd\u591f\u8868\u73b0\u51fa\u4e0d\u540c\u7269\u7406\u884c\u4e3a\u7684\u3001\u4e0d\u540c\u79cd\u7c7b\u7684\u795e\u7ecf\u7f51\u7edc\u667a\u80fd\u4f53\u3002\u6700\u8fd1\uff0c\u5f00\u53d1\u5de5\u4f5c\u5df2\u7ecf\u8fc1\u79fb\u5230PettingZoo[67]\u591a\u667a\u80fd\u4f53\u5f3a\u5316\u5b66\u4e60\u9879\u76ee\u4e0a\u3002<\/span><\/section>\n
 <\/span><\/section>\n
<\/section>\n
 <\/span><\/section>\n

\u56fe8. MAgent[74]\u662f\u4e00\u5957\u73af\u5883\uff0c\u5728\u7f51\u683c\u4e16\u754c\u4e2d\uff0c\u5927\u91cf\u7684\u50cf\u7d20\u7ea7\u667a\u80fd\u4f53\u5728\u6218\u6597\u6216\u5176\u4ed6\u7ade\u4e89\u573a\u666f\u4e2d\u4e92\u52a8\u3002\u4e0e\u5927\u591a\u6570\u4e13\u6ce8\u4e8e\u5355\u4e00\u667a\u80fd\u4f53\u6216\u53ea\u6709\u5c11\u6570\u667a\u80fd\u4f53\u7684\u5f3a\u5316\u5b66\u4e60\u7814\u7a76\u5e73\u53f0\u4e0d\u540c\uff0cMAgent\u65e8\u5728\u4e3a\u6269\u5c55\u5230\u6570\u767e\u4e07\u667a\u80fd\u4f53\u7684\u5f3a\u5316\u5b66\u4e60\u7814\u7a76\u63d0\u4f9b\u652f\u6301\u3002\u8fd9\u4e2a\u5e73\u53f0\u7684\u73af\u5883\u73b0\u5728\u4f5c\u4e3aPettingZoo[67]\u5f00\u6e90\u5e93\u7684\u4e00\u90e8\u5206\u8fdb\u884c\u7ef4\u62a4\uff0c\u7528\u4e8e\u591a\u667a\u80fd\u4f53\u5f3a\u5316\u5b66\u4e60\u7684\u7814\u7a76\u3002<\/span><\/p>\n

 <\/span><\/section>\n
\u53d7\u5230\u5927\u578b\u591a\u4eba\u5728\u7ebf\u89d2\u8272\u626e\u6f14\u6e38\u620f<\/span>\uff08Massively Multiplayer Online Role-Playing Games, MMORPGs, \u53c8\u79f0MMOs\uff09<\/span>\u7684\u542f\u53d1\uff0cNeural MMO[63]\u51fa\u73b0\u4e86\uff0c\u5b83\u662f\u4e00\u4e2a\u652f\u6301\u5927\u91cf\u4eba\u5de5\u667a\u80fd\u4f53\u7684\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u73af\u5883\u3002\u8fd9\u4e9b\u667a\u80fd\u4f53\u4e3a\u4e86\u751f\u5b58\uff0c\u5fc5\u987b\u7ade\u4e89\u6709\u9650\u7684\u8d44\u6e90\u3002\u56e0\u6b64\uff0c\u8be5\u73af\u5883\u80fd\u591f\u5927\u89c4\u6a21\u5730\u6a21\u62df\u591a\u667a\u80fd\u4f53\u7684\u4e92\u52a8\uff0c\u8981\u6c42\u667a\u80fd\u4f53\u4e0e\u7fa4\u4f53\u5185\u7684\u5176\u5b83\uff08\u540c\u6837\u65e8\u5728\u4e89\u593a\u8d44\u6e90\u7684\uff09\u667a\u80fd\u4f53\u4e00\u8d77\u5b66\u4e60\u6218\u6597\u548c\u5bfc\u822a\u7684\u7b56\u7565\u3002\u4e0e\u5927\u591a\u6570\u591a\u667a\u80fd\u4f53\u5f3a\u5316\u5b66\u4e60\u73af\u5883\u4e0d\u540c\u7684\u662f\uff0c\u8be5\u73af\u5883\u5141\u8bb8\u6bcf\u4e2a\u667a\u80fd\u4f53\u6709\u81ea\u5df1\u72ec\u7279\u7684\u795e\u7ecf\u7f51\u7edc\u6743\u91cd\u96c6\uff0c\u8fd9\u5728\u5185\u5b58\u6d88\u8017\u65b9\u9762\u662f\u4e00\u4e2a\u6280\u672f\u6311\u6218\u3002\u8be5\u5e73\u53f0\u65e9\u671f\u7248\u672c\u7684\u521d\u6b65\u5b9e\u9a8c\u7ed3\u679c[62]\u8868\u660e\uff0c\u5177\u6709\u4e0d\u540c\u795e\u7ecf\u7f51\u7edc\u6743\u91cd\u7684\u667a\u80fd\u4f53\u53d1\u5c55\u4e86\u586b\u8865\u4e0d\u540c\u58c1\u9f9b\u7684\u6280\u80fd\uff0c\u6765\u907f\u514d\u5728\u5927\u91cf\u667a\u80fd\u4f53\u7fa4\u4f53\u4e2d\u7684\u7ade\u4e89\u3002\u622a\u81f3\u53d1\u7a3f\u65f6\uff0c\u8fd9\u4e2a\u9879\u76ee\u6b63\u5728NeurIPS\u673a\u5668\u5b66\u4e60\u793e\u533a[63]\u4e2d\u88ab\u79ef\u6781\u5f00\u53d1\uff0c\u81f4\u529b\u4e8e\u5927\u89c4\u6a21\u667a\u80fd\u4f53\u7fa4\u4f53\u3001\u957f\u65f6\u95f4\u8de8\u5ea6\u3001\u5f00\u653e\u5f0f\u4efb\u52a1\u548c\u6a21\u5757\u5316\u6e38\u620f\u7cfb\u7edf\u7b49\u65b9\u9762\u7684\u7814\u7a76\u3002\u4e3a\u5b9e\u73b0\u8fd9\u4e00\u5927\u89c4\u6a21\u3001\u591a\u667a\u80fd\u4f53\u7684\u7814\u7a76\u8def\u5f84\uff0c\u5f00\u53d1\u8005\u63d0\u4f9b\u4e86\u79ef\u6781\u7684\u652f\u6301\u3001\u5145\u8db3\u7684\u6587\u6863\uff0c\u8fd8\u5f00\u53d1\u4e86\u989d\u5916\u7684\u8bad\u7ec3\u3001\u8bb0\u5f55\u548c\u53ef\u89c6\u5316\u5de5\u5177\u3002<\/span><\/section>\n
 <\/span><\/section>\n
<\/section>\n

\u56fe9. Neural MMO[63]\u662f\u4e00\u4e2a\u5728\u7a0b\u5e8f\u5316\u751f\u6210\u7684\u865a\u62df\u4e16\u754c\u4e2d\u6a21\u62df\u667a\u80fd\u4f53\u7fa4\u4f53\u7684\u5e73\u53f0\uff0c\u65e8\u5728\u4e3a\u591a\u667a\u80fd\u4f53\u7814\u7a76\u63d0\u4f9b\u652f\u6301\uff0c\u5e76\u5c06\u5176\u5bf9\u8ba1\u7b97\u8d44\u6e90\u7684\u8981\u6c42\u9650\u5236\u5728\u4e00\u5b9a\u8303\u56f4\u5185\u3002\u7528\u6237\u53ef\u4ee5\u4ece\u4e00\u7ec4\u5e73\u53f0\u63d0\u4f9b\u7684\u6e38\u620f\u7cfb\u7edf\u4e2d\u9009\u62e9\uff0c\u4e3a\u4ed6\u4eec\u5177\u4f53\u7684\u7814\u7a76\u95ee\u9898\u521b\u9020\u73af\u5883\u2014\u2014\u5e73\u53f0\u652f\u6301\u591a\u8fbe\u4e00\u5343\u79cd\u667a\u80fd\u4f53\u3001\u4e00\u5e73\u65b9\u516c\u91cc\u7684\u5730\u56fe\u4ee5\u53ca\u51e0\u5343\u4e2a\u65f6\u95f4\u6b65\u957f\u3002\u8be5\u9879\u76ee\u6b63\u5728\u79ef\u6781\u5f00\u53d1\u4e2d\uff0c\u6709\u5927\u91cf\u7684\u6587\u6863\u548c\u5de5\u5177\uff0c\u4e3a\u7814\u7a76\u4eba\u5458\u63d0\u4f9b\u8bb0\u5f55\u548c\u53ef\u89c6\u5316\u5de5\u5177\u3002\u5728\u53d1\u7a3f\u65f6\uff0c\u8fd9\u4e2a\u5e73\u53f0\u5373\u5c06\u57282021\u5e74\u7684NeurIPS\u4f1a\u8bae\u4e0a\u8fdb\u884c\u6f14\u793a\u3002<\/span><\/p>\n

 <\/span><\/section>\n

\n
4\u3001\u5143\u5b66\u4e60<\/span><\/strong><\/span><\/section>\n<\/h4>\n

<\/section>\n
\u5728\u524d\u9762\u7684\u7ae0\u8282\u4e2d\uff0c\u6211\u4eec\u63cf\u8ff0\u4e86\u4e00\u4e9b\u7814\u7a76\uff0c\u5b83\u4eec\u7ed9\u51fa\u4e86\u89e3\u51b3\u65b9\u6848\u2014\u2014\u8ba9\u72ec\u7acb\u7684\u795e\u7ecf\u7f51\u7edc\u667a\u80fd\u4f53\u7684\u96c6\u5408\u534f\u540c\u5de5\u4f5c\uff0c\u6765\u5b9e\u73b0\u5171\u540c\u76ee\u6807\u3002\u8fd9\u4e9b\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u7684\u53c2\u6570\uff0c\u9488\u5bf9\u7fa4\u4f53\u7684\u96c6\u4f53\u8868\u73b0\u8fdb\u884c\u4e86\u4f18\u5316\u3002\u867d\u7136\u8fd9\u4e9b\u7cfb\u7edf\u5df2\u7ecf\u88ab\u8bc1\u660e\u662f\u7a33\u5065\u7684\uff0c\u800c\u4e14\u80fd\u9002\u5e94\u73af\u5883\u7684\u53d8\u5316\uff0c\u4f46\u5f52\u6839\u7ed3\u5e95\uff0c\u5b83\u4eec\u8fd8\u662f\u88ab\u5f3a\u884c\u89c4\u5b9a\u8981\u6267\u884c\u67d0\u4e2a\u7279\u5b9a\u4efb\u52a1\uff0c\u4e0d\u80fd\u6539\u53d8\u3002\u4f8b\u5982\uff0c\u4e00\u4e2a\u88ab\u8bad\u7ec3\u6210\u5411\u524d\u79fb\u52a8\u7684\u7cfb\u7edf\uff0c\u5728\u4e0d\u91cd\u65b0\u8bad\u7ec3\u7684\u60c5\u51b5\u4e0b\uff0c\u4e0d\u80fd\u7a81\u7136\u6267\u884c\u53e6\u4e00\u4e2a\u5b8c\u5168\u4e0d\u540c\u7684\u4efb\u52a1\uff0c\u5982\u5411\u4e0a\u8df3\u8dc3\u3002\u4e3a\u4e86\u6267\u884c\u53e6\u4e00\u4e2a\u4efb\u52a1\uff0c\u7cfb\u7edf\u5fc5\u987b\u80fd\u591f\u5728\u90e8\u7f72\u8fc7\u7a0b\u4e2d\u4e0d\u65ad\u5730\u4ece\u7ecf\u9a8c\u4e2d\u5b66\u4e60\u3002\u867d\u7136\u4eba\u4eec\u53ef\u4ee5\u7b80\u5355\u5730\u65f6\u4e0d\u65f6\u6682\u505c\u7cfb\u7edf\uff0c\u624b\u52a8\u5730\u901a\u8fc7\u6700\u65b0\u6570\u636e\u91cd\u65b0\u8bad\u7ec3\u5b83\uff0c\u4f46\u53e6\u4e00\u79cd\u65b9\u6cd5\u662f\u8ba9\u7cfb\u7edf\u80fd\u591f\u81ea\u5df1\u5b66\u4e60\u3002\u5143\u5b66\u4e60\u662f\u6df1\u5ea6\u5b66\u4e60\u4e2d\u4e00\u4e2a\u6d3b\u8dc3\u7684\u7814\u7a76\u9886\u57df\uff0c\u5176\u76ee\u6807\u662f\u8bad\u7ec3\u7cfb\u7edf\u7684\u5b66\u4e60\u80fd\u529b\u3002\u4f20\u7edf\u4e0a\uff0c\u795e\u7ecf\u7f51\u7edc\u662f\u901a\u8fc7\u68af\u5ea6\u4e0b\u964d\u7b97\u6cd5\u6216\u8005\u8fdb\u5316\u7b56\u7565\u6765\u4f18\u5316\u5176\u6743\u91cd\u53c2\u6570\uff0c\u4ee5\u5b8c\u6210\u4e00\u9879\u7279\u5b9a\u4efb\u52a1\u3002\u800c\u5143\u5b66\u4e60\u7684\u76ee\u6807\u662f\u8bad\u7ec3\u4e00\u4e2a\u5143\u5b66\u4e60\u8005\uff0c\u6216\u8005\u5b66\u4e60\u4e00\u79cd\u5b66\u4e60\u7b97\u6cd5<\/strong>\u3002\u5728\u8fd9\u4e00\u8282\u4e2d\uff0c\u6211\u4eec\u5c06\u8ba8\u8bba\u96c6\u4f53\u667a\u80fd\u4f53\uff0c\u5b83\u4eec\u88ab\u8fde\u63a5\u8d77\u6765\u5b66\u4e60\uff0c\u800c\u4e0d\u662f\u8fde\u63a5\u8d77\u6765\u6267\u884c\u4e00\u9879\u7279\u5b9a\u7684\u4efb\u52a1\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6765\u81ea\u81ea\u7ec4\u7ec7\u7684\u6982\u5ff5\uff0c\u53ef\u4ee5\u901a\u8fc7\u6269\u5c55\u6784\u6210\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u57fa\u672c\u6784\u5efa\uff0c\u5f88\u81ea\u7136\u5730\u5e94\u7528\u5230\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc\u7684\u8fc7\u7a0b\u4e2d\uff0c\u8ba9\u5b83\u8fdb\u884c\u5143\u5b66\u4e60\u3002\u6b63\u5982\u6211\u4eec\u6240\u77e5\u9053\u7684\uff0c\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7531\u76f8\u540c\u7684\u795e\u7ecf\u5143\u7ec4\u6210\uff0c\u8fd9\u4e9b\u795e\u7ecf\u5143\u88ab\u5efa\u6a21\u6210\u975e\u7ebf\u6027\u7684\u6fc0\u6d3b\u51fd\u6570\uff0c\u5728\u7f51\u7edc\u4e2d\u901a\u8fc7\u7a81\u89e6<\/span>\uff08\u6743\u91cd\u53c2\u6570\uff09<\/span>\u8fde\u63a5\uff0c\u901a\u5e38\u7528\u68af\u5ea6\u4e0b\u964d\u7b49\u5b66\u4e60\u7b97\u6cd5\u8bad\u7ec3\u3002\u4f46\u4eba\u4eec\u4e0d\u96be\u60f3\u8c61\uff0c\u795e\u7ecf\u5143\u548c\u7a81\u89e6\u7684\u62bd\u8c61\u4e5f\u53ef\u4ee5\u62d3\u5c55\u5230\u9759\u6001\u6fc0\u6d3b\u51fd\u6570\u548c\u6d6e\u70b9\u53c2\u6570\u4e4b\u5916\u3002\u4e8b\u5b9e\u4e0a\uff0c\u6700\u8fd1\u7684\u7814\u7a76[40,42]\u5df2\u7ecf\u8bd5\u56fe\u5c06\u795e\u7ecf\u7f51\u7edc\u7684\u6bcf\u4e2a\u795e\u7ecf\u5143\u5efa\u6a21\u4e3a\u4e00\u4e2a\u5355\u72ec\u7684\u5f3a\u5316\u5b66\u4e60\u667a\u80fd\u4f53\u3002\u7528\u5f3a\u5316\u5b66\u4e60\u7684\u672f\u8bed\u6765\u8bf4\uff0c\u6bcf\u4e2a\u795e\u7ecf\u5143\u7684\u201c\u89c2\u6d4b\u201d\u662f\u5b83\u81ea\u5df1\u7684\u5f53\u524d\u72b6\u6001\uff0c\u8be5\u72b6\u6001\u968f\u7740\u4fe1\u606f\u5728\u7f51\u7edc\u4e2d\u7684\u4f20\u9012\u800c\u53d8\u5316\uff0c\u800c\u6bcf\u4e2a\u795e\u7ecf\u5143\u7684\u201c\u52a8\u4f5c\u201d\uff0c\u4f7f\u5f97\u6bcf\u4e2a\u795e\u7ecf\u5143\u80fd\u591f\u4fee\u6539\u5b83\u4e0e\u7cfb\u7edf\u4e2d\u5176\u5b83\u795e\u7ecf\u5143\u7684\u8fde\u63a5\u3002\u56e0\u6b64\uff0c\u5b66\u4e60\u5982\u4f55\u5b66\u4e60\u7684\u95ee\u9898\uff0c\u88ab\u89c6\u4e3a\u4e00\u4e2a\u591a\u667a\u80fd\u4f53\u7684\u5f3a\u5316\u5b66\u4e60\u95ee\u9898\uff0c\u6bcf\u4e2a\u667a\u80fd\u4f53\u662f\u795e\u7ecf\u7f51\u7edc\u4e2d\u795e\u7ecf\u5143\u96c6\u5408\u7684\u4e00\u90e8\u5206\u3002\u867d\u7136\u8fd9\u79cd\u65b9\u6cd5\u5f88\u4f18\u96c5\uff0c\u4f46\u4e0a\u8ff0\u7814\u7a76\u53ea\u80fd\u591f\u89e3\u51b3\u73a9\u5177\u95ee\u9898\uff0c\u4e0d\u80fd\u4e0e\u73b0\u6709\u7684\u5b66\u4e60\u7b97\u6cd5\u7ade\u4e89\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6700\u8fd1\u7684\u65b9\u6cd5\u5df2\u7ecf\u4e0d\u518d\u7b80\u5355\u5730\u4f7f\u7528\u6807\u91cf\u6743\u91cd\u5728\u795e\u7ecf\u5143\u4e4b\u95f4\u4f20\u8f93\u6807\u91cf\u4fe1\u53f7\u4e86\u3002Sandler\u7b49\u4eba[55]\u5f15\u5165\u4e86\u4e00\u79cd\u65b0\u578b\u7684\u5e7f\u4e49\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff0c\u5176\u795e\u7ecf\u5143\u548c\u7a81\u89e6\u90fd\u6709\u591a\u79cd\u72b6\u6001\u3002\u4f20\u7edf\u7684\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u53ef\u4ee5\u88ab\u770b\u505a\u662f\u8be5\u6846\u67b6\u7684\u4e00\u4e2a\u7279\u4f8b\uff0c\u6709\u4e24\u4e2a\u72b6\u6001\uff0c\u4e00\u4e2a\u7528\u4e8e\u6fc0\u6d3b\uff0c\u53e6\u4e00\u4e2a\u7528\u4e8e\u53cd\u5411\u4f20\u64ad\u89c4\u5219\u4ea7\u751f\u7684\u68af\u5ea6\u3002\u5728\u901a\u7528\u7684\u6846\u67b6\u4e2d\uff0c\u5b83\u4eec\u4e0d\u9700\u8981\u53cd\u5411\u4f20\u64ad\u7a0b\u5e8f\u6765\u8ba1\u7b97\u4efb\u4f55\u68af\u5ea6\uff0c\u800c\u662f\u4f9d\u9760\u4e00\u4e2a\u5171\u4eab\u7684\u5c40\u90e8\u5b66\u4e60\u89c4\u5219\u6765\u66f4\u65b0\u7a81\u89e6\u548c\u795e\u7ecf\u5143\u7684\u72b6\u6001\u3002\u8fd9\u79cdHebbian\u5f0f\u7684\u53cc\u5411\u5c40\u90e8\u66f4\u65b0\u89c4\u5219\u53ea\u9700\u8981\u6bcf\u4e2a\u795e\u7ecf\u5143\u4e0e\u7a81\u89e6\u4ece\u5b83\u4eec\u7684\u76f8\u90bb\u795e\u7ecf\u5143\u4e0e\u7a81\u89e6\u83b7\u53d6\u4fe1\u606f\uff0c\u7c7b\u4f3c\u5143\u80de\u81ea\u52a8\u673a\u3002\u8be5\u89c4\u5219\u88ab\u53c2\u6570\u5316\u4e3a\u4e00\u4e2a\u4f4e\u7ef4\u7684\u57fa\u56e0\u7ec4\u5411\u91cf\uff0c\u800c\u4e14\u5728\u6574\u4e2a\u7cfb\u7edf\u4e2d\u662f\u4e00\u81f4\u7684\u3002\u4ed6\u4eec\u91c7\u7528\u4e86\u6f14\u5316\u7b56\u7565\u6216\u4f20\u7edf\u7684\u4f18\u5316\u6280\u672f\u6765\u5143\u5b66\u4e60\u8fd9\u4e2a\u57fa\u56e0\u7ec4\u5411\u91cf\u3002\u4ed6\u4eec\u4e3b\u8981\u7684\u7ed3\u679c\u662f\uff1a\u5728\u8bad\u7ec3\u4efb\u52a1\u4e0a\u5143\u5b66\u4e60\u7684\u66f4\u65b0\u89c4\u5219\uff0c\u53ef\u4ee5\u6cdb\u5316\u5230\u65b0\u7684\u672a\u89c1\u8fc7\u7684\u6d4b\u8bd5\u4efb\u52a1\u3002\u6b64\u5916\uff0c\u5728\u4e00\u4e9b\u6807\u51c6\u7684\u5206\u7c7b\u4efb\u52a1\u4e2d\uff0c\u66f4\u65b0\u89c4\u5219\u6bd4\u57fa\u4e8e\u68af\u5ea6\u4e0b\u964d\u7684\u5b66\u4e60\u7b97\u6cd5\u66f4\u5feb\u3002<\/span><\/section>\n
 <\/span><\/section>\n
Kirsch\u7b49\u4eba\u4e5f\u91c7\u53d6\u4e86\u7c7b\u4f3c\u7684\u505a\u6cd5[33]\uff0c\u5c06\u795e\u7ecf\u7f51\u7edc\u7684\u795e\u7ecf\u5143\u548c\u7a81\u89e6\u6cdb\u5316\u4e3a\u66f4\u9ad8\u7ef4\u5ea6\u7684\u4fe1\u606f\u4f20\u9012\u7cfb\u7edf\u3002\u4f46\u5728\u4ed6\u4eec\u7684\u6848\u4f8b\u91cc\uff0c\u6bcf\u4e2a\u7a81\u89e6\u88ab\u4e00\u4e2a\u5177\u6709\u76f8\u540c\u5171\u4eab\u53c2\u6570\u7684\u5faa\u73af\u795e\u7ecf\u7f51\u7edc<\/span>\uff08recurrent neural network, RNN\uff09<\/span>\u6240\u53d6\u4ee3\u3002\u8fd9\u4e9b\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\u7a81\u89e6\u662f\u53cc\u5411\u7684\uff0c\u652f\u914d\u7740\u6574\u4e2a\u7f51\u7edc\u7684\u4fe1\u606f\u6d41\u3002\u4e0eSandler\u7b49\u4eba\u7684\u7814\u7a76[55]\u4e00\u6837\uff0c\u8fd9\u79cd\u53cc\u5411\u6027\u4f7f\u5f97\u7f51\u7edc\u65e2\u80fd\u63a8\u7406\u548c\u5b66\u4e60\uff0c\u53c8\u80fd\u5728\u524d\u5411\u4f20\u64ad\u6a21\u5f0f\u4e0b\u8fd0\u884c\u3002\u8fd9\u4e2a\u7cfb\u7edf\u7684\u6743\u91cd\u57fa\u672c\u4e0a\u5b58\u50a8\u4e8e\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\u7684\u9690\u85cf\u72b6\u6001\u4e2d\uff0c\u6240\u4ee5\u901a\u8fc7\u7b80\u5355\u7684\u8fd0\u884c\uff0c\u8be5\u7cfb\u7edf\u53ef\u4ee5\u4f7f\u7528\u9519\u8bef\u4fe1\u53f7\u4f5c\u4e3a\u53cd\u9988\u6765\u8bad\u7ec3\u81ea\u5df1\u3002\u7531\u4e8e\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\u662f\u901a\u7528\u8ba1\u7b97\u5668\uff0c\u4ed6\u4eec\u80fd\u591f\u8bc1\u660e\uff0c\u8be5\u7cfb\u7edf\u53ef\u4ee5\u7f16\u7801\u57fa\u4e8e\u68af\u5ea6\u7684\u53cd\u5411\u4f20\u64ad\u7b97\u6cd5\uff0c\u901a\u8fc7\u88ab\u8bad\u7ec3\u6765\u7b80\u5355\u5730\u6a21\u62df\u53cd\u5411\u4f20\u64ad\uff0c\u800c\u4e0d\u662f\u901a\u8fc7\u624b\u52a8\u8bbe\u8ba1\u660e\u786e\u5730\u8ba1\u7b97\u68af\u5ea6\u3002\u5f53\u7136\uff0c\u4ed6\u4eec\u7684\u7cfb\u7edf\u6bd4\u53cd\u5411\u4f20\u64ad\u8981\u901a\u7528\u5f97\u591a\uff0c\u56e0\u6b64\u80fd\u591f\u5b66\u4e60\u6bd4\u53cd\u5411\u4f20\u64ad\u66f4\u6709\u6548\u7684\u65b0\u5b66\u4e60\u7b97\u6cd5<\/span>\uff08\u89c1\u56fe10\uff09<\/span>\u3002<\/span><\/section>\n
 <\/span><\/section>\n
<\/section>\n

\u56fe10. Sandler\u7b49\u4eba[55]\u548cKirsch\u7b49\u4eba[33]\u7684\u6700\u8fd1\u7814\u7a76\u5de5\u4f5c\uff0c\u8bd5\u56fe\u6cdb\u5316\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u516c\u8ba4\u6982\u5ff5\uff0c\u4f7f\u6bcf\u4e2a\u795e\u7ecf\u5143\u53ef\u4ee5\u6709\u591a\u4e2a\u72b6\u6001\uff0c\u800c\u4e0d\u662f\u4e00\u4e2a\u6807\u91cf\u503c\uff0c\u4e5f\u4f7f\u6bcf\u4e2a\u7a81\u89e6\u7684\u529f\u80fd\u662f\u53cc\u5411\u7684\uff0c\u6765\u4fc3\u8fdb\u5b66\u4e60\u548c\u63a8\u7406\u3002\u5982\u672c\u56fe\u6240\u793a\uff0cKirsch\u7b49\u4eba[33]\u63d0\u51fa\u7528\u4e00\u4e2a\u7b80\u5355\u7684\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\uff08\u5177\u6709\u4e0d\u540c\u7684\u5185\u90e8\u9690\u85cf\u72b6\u6001\uff09\u6765\u6a21\u62df\u6bcf\u4e2a\u7a81\u89e6\uff0c\u5e76\u6807\u660e\u7f51\u7edc\u53ef\u4ee5\u901a\u8fc7\u7b80\u5355\u5730\u8fd0\u884c\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\u5355\u5143\u6765\u8bad\u7ec3\uff0c\u800c\u4e0d\u662f\u4f7f\u7528\u53cd\u5411\u4f20\u64ad\u3002<\/span><\/p>\n

 <\/span><\/section>\n
\u524d\u8ff0\u4e24\u9879\u5de5\u4f5c\uff0c\u5728\u672c\u6587\u5199\u4f5c\u65f6\u624d\u521a\u521a\u53d1\u8868\u3002\u6211\u4eec\u76f8\u4fe1\uff0c\u8fd9\u4e9b\u5206\u6563\u7684\u5c40\u90e8\u5143\u5b66\u4e60\u65b9\u6cd5\uff0c\u6709\u53ef\u80fd\u5728\u672a\u6765\u5f7b\u5e95\u6539\u53d8\u795e\u7ecf\u7f51\u7edc\u7684\u4f7f\u7528\u65b9\u5f0f\uff0c\u6311\u6218\u76ee\u524d\u6a21\u578b\u8bad\u7ec3\u4e0e\u6a21\u578b\u90e8\u7f72\u5206\u79bb\u7684\u8303\u5f0f\u3002\u4e0d\u8fc7\uff0c\u8981\u8bc1\u660e\u8fd9\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u6269\u5c55\u5230\u66f4\u5927\u7684\u6570\u636e\u96c6\uff0c\u6211\u4eec\u8fd8\u6709\u8bb8\u591a\u5de5\u4f5c\u8981\u505a\uff0c\u6bd5\u7adf\u8fd9\u4e9b\u65b9\u6cd5\u6709\u66f4\u5927\u7684\u5185\u5b58\u9700\u6c42<\/span>\uff08\u56e0\u4e3a\u7cfb\u7edf\u6709\u5927\u5f97\u591a\u7684\u5185\u90e8\u72b6\u6001\uff09<\/span>\u3002\u6b64\u5916\uff0c\u867d\u7136\u8fd9\u4e9b\u7b97\u6cd5\u80fd\u591f\u4ea7\u751f\u6bd4\u68af\u5ea6\u4e0b\u964d\u66f4\u4e3a\u6709\u6548\u7684\u5b66\u4e60\u7b97\u6cd5\uff0c\u4f46\u8fd9\u79cd\u6709\u6548\u6027\u53ea\u5728\u5b66\u4e60\u7684\u65e9\u671f\u9636\u6bb5\u660e\u663e\uff0c\u7f51\u7edc\u6027\u80fd\u4e5f\u5f88\u5feb\u5c31\u6536\u655b\u4e86\u3002\u800c\u68af\u5ea6\u4e0b\u964d\u867d\u7136\u6548\u7387\u8f83\u4f4e\uff0c\u4f46\u5728\u5c0f\u6837\u672c\u5b66\u4e60\u65f6\u504f\u5dee\u8f83\u5c0f\uff0c\u800c\u4e14\u53ef\u4ee5\u7ee7\u7eed\u8fd0\u884c\u66f4\u591a\u8f6e\uff0c\u6765\u5b8c\u5584\u6743\u91cd\u53c2\u6570\uff0c\u6700\u7ec8\u4ea7\u751f\u7684\u7f51\u7edc\u5c06\u53d6\u5f97\u66f4\u9ad8\u7684\u6027\u80fd\u3002<\/span><\/section>\n
 <\/span><\/section>\n


<\/p>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u56db\u3001\u6df1\u5ea6\u5b66\u4e60\u7528\u4e8e\u96c6\u4f53\u667a\u80fd<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u5230\u76ee\u524d\u4e3a\u6b62\uff0c\u6211\u4eec\u8ba8\u8bba\u4e86\u5df2\u7ecf\u88ab\u7eb3\u5165\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u4e2d\u7684\u6765\u81ea\u96c6\u4f53\u667a\u80fd\u7684\u65b9\u6cd5\u3002\u5b83\u4eec\u4e3a\u57fa\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u7cfb\u7edf\u6253\u5f00\u4e86\u8bb8\u591a\u8010\u4eba\u5bfb\u5473\u7684\u5927\u95e8\u3002\u4f46\u662f\uff0c\u6b63\u5982\u751f\u7269\u795e\u7ecf\u7f51\u7edc\u53ea\u662f\u5728\u6700\u521d\u542f\u53d1\u4e86\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u4e00\u6837\uff0c\u53d8\u6210\u4e00\u4e2a\u4eba\u5de5\u5927\u8111\u4e5f\u5e76\u4e0d\u662f\u6df1\u5ea6\u5b66\u4e60\u7684\u6700\u540e\u7ed3\u679c\uff0c\u81f3\u5c11\u73b0\u5728\u8fd8\u4e0d\u662f\u3002\u4e0d\u8fc7\uff0c\u6df1\u5ea6\u5b66\u4e60\u4e3a\u751f\u6210\u6027\u5efa\u6a21\u548c\u7edf\u8ba1\u5206\u6790\u5f00\u53d1\u4e86\u4ee4\u4eba\u96be\u4ee5\u7f6e\u4fe1\u7684\u5f3a\u5927\u5de5\u5177\u3002\u5728\u751f\u7269\u5b66\u4e2d\uff0c\u6211\u4eec\u5df2\u7ecf\u770b\u5230\u795e\u7ecf\u79d1\u5b66\u5bb6\u5f00\u59cb\u91c7\u7528\u6df1\u5ea6\u5b66\u4e60\u7684\u5de5\u5177\uff0c\u53cd\u8fc7\u6765\u7528\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u5206\u6790\u751f\u7269\u795e\u7ecf\u7f51\u7edc[43]\u3002\u540c\u6837\u7684\u9053\u7406\uff0c\u6211\u4eec\u4e5f\u89c2\u5bdf\u5230\u6709\u4e9b\u7814\u7a76\u5f00\u59cb\u8fd0\u7528\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\uff0c\u4f7f\u6211\u4eec\u66f4\u597d\u5730\u7406\u89e3\u590d\u6742\u7cfb\u7edf\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u6211\u4eec\u5076\u5c14\u53ef\u4ee5\u53d1\u73b0\u590d\u6742\u52a8\u529b\u7cfb\u7edf\u7684\u5c40\u90e8\u89c4\u5219\u4e2d\u56e0\u81ea\u7ec4\u7ec7\u800c\u51fa\u73b0\u7684\u6709\u8da3\u6a21\u5f0f\u3002\u4f46\u5bf9\u4e8e\u7814\u7a76\u4eba\u5458\u548c\u4e1a\u4f59\u7231\u597d\u8005\u6765\u8bf4\uff0c\u8981\u627e\u5230\u8fd9\u4e9b\u6a21\u5f0f\u662f\u4e00\u4e2a\u8017\u65f6\u7684\u8fc7\u7a0b\uff0c\u8fd9\u4e2a\u8fc7\u7a0b\u4f9d\u8d56\u4e8e\u542f\u53d1\u5f0f\u7684\u65b9\u6cd5\u548c\u5bf9\u5c40\u90e8\u89c4\u5219\u7684\u521d\u59cb\u72b6\u6001\u548c\u53c2\u6570\u7684\u624b\u52a8\u8c03\u8282\u3002\u5728\u672c\u8282\u4e2d\uff0c\u6211\u4eec\u5c06\u8ba8\u8bba\u4e00\u4e9b\u7814\u7a76\uff0c\u4f7f\u7528\u6df1\u5ea6\u5b66\u4e60\u6765\u5206\u6790\u5143\u80de\u81ea\u52a8\u673a\u7684\u4e30\u5bcc\u6d8c\u73b0\u884c\u4e3a\u7684\u590d\u6742\u6a21\u5f0f\u3002Zenil\u7b49\u4eba\u7684\u65e9\u671f\u7814\u7a76[72]\uff0c\u63d0\u51fa\u4f7f\u7528\u538b\u7f29\u6765\u91cf\u5316\u4e00\u4e2a\u5143\u80de\u81ea\u52a8\u673a\u76f8\u53d8\u7684\u53ef\u9884\u6d4b\u6027\u3002\u4ed6\u4eec\u8868\u660e\uff0c\u57fa\u4e8e\u538b\u7f29\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5c06Wolfram\u7684\u89c4\u5219[70]\u5f52\u5165\u4e0eWolfram\u4ee5\u524d\u7814\u7a76\u7684\u542f\u53d1\u5f0f\u884c\u4e3a\u76f8\u5bf9\u5e94\u7684\u7fa4\u7ec4\u3002\u8fd9\u9879\u65e9\u671f\u7814\u7a76\u8868\u660e\uff0c\u5982\u679c\u9884\u6d4b\u5143\u80de\u81ea\u52a8\u673a\u884c\u4e3a\u7684\u96be\u5ea6\u88ab\u91cf\u5316\uff0c\u8fd9\u4e9b\u6570\u503c\u53ef\u4ee5\u4f5c\u4e3a\u7814\u7a76\u5143\u80de\u81ea\u52a8\u673a\u548c\u5176\u5b83\u590d\u6742\u7cfb\u7edf\u52a8\u6001\u7279\u6027\u7684\u66f4\u5e7f\u6cdb\u6846\u67b6\u7684\u4e00\u90e8\u5206\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u5728\u6700\u8fd1\u7684\u4e00\u9879\u7814\u7a76\u4e2d\uff0cCisneros\u7b49\u4eba[13]\u7814\u7a76\u4e86\u51e0\u4e2a\u8861\u91cf\u590d\u6742\u7cfb\u7edf<\/span>\uff08\u5982\u5143\u80de\u81ea\u52a8\u673a\uff09<\/span>\u4e2d\u6d8c\u73b0\u6a21\u5f0f\u590d\u6742\u5ea6\u589e\u957f\u7684\u6307\u6807\u3002\u4ed6\u4eec\u8ba4\u4e3a\uff0c\u8861\u91cf\u8fd9\u79cd\u589e\u957f\u7684\u6307\u6807\uff0c\u5bf9\u4e8e\u8bbe\u8ba1\u80fd\u5c55\u73b0\u51fa\u5f00\u653e\u5f0f\u6f14\u5316\u7684\u7cfb\u7edf\u662f\u5f88\u6709\u7528\u7684\u3002\u9664\u4e86\u57fa\u4e8e\u538b\u7f29\u7684\u5ea6\u91cf\uff0c\u4ed6\u4eec\u8fd8\u63d0\u51fa\u4f7f\u7528\u7ecf\u8fc7\u8bad\u7ec3\u7684\u795e\u7ecf\u7f51\u7edc\u6765\u9884\u6d4b\u5143\u80de\u81ea\u52a8\u673a\u7684\u884c\u4e3a\u3002\u5728\u4e00\u7ef4\u548c\u4e8c\u7ef4\u7f51\u683c\u4e0a\uff0c\u4f7f\u7528\u57fa\u4e8e\u795e\u7ecf\u7684\u5ea6\u91cf\uff0c\u4ed6\u4eec\u80fd\u591f\u81ea\u52a8\u6784\u5efa\u8ba1\u7b97\u6a21\u578b\uff0c\u6709\u7740\u5eb7\u5a01\u751f\u547d\u6e38\u620f\u4e2d\u53d1\u73b0\u7684\u6d8c\u73b0\u5c5e\u6027[14]\u3002\u4ed6\u4eec\u7684\u65b9\u6cd5\u53ef\u4ee5\u5e94\u7528\u4e8e\u5e7f\u6cdb\u7684\u590d\u6742\u7cfb\u7edf\uff0c\u4e0d\u5c40\u9650\u4e8e\u5143\u80de\u81ea\u52a8\u673a\u3002<\/span><\/section>\n

<\/section>\n
\u5386\u53f2\u4e0a\uff0c\u5143\u80de\u81ea\u52a8\u673a\u53d7\u9650\u4e8e\u53ea\u80fd\u5728\u79bb\u6563\u65f6\u95f4\u548c\u79bb\u6563\u7a7a\u95f4\u4e2d\u8fd0\u884c\u7684\u89c4\u5219\u3002\u6700\u8fd1\uff0cChan\u5f00\u53d1\u4e86\u4e00\u4e2a\u540d\u4e3aLenia\u7684\u65b0\u7684\u4eba\u5de5\u751f\u547d\u7cfb\u7edf[6,7]\u3002\u8fd9\u662f\u4e00\u4e2a\u5177\u6709\u8fde\u7eed\u65f6\u7a7a\u72b6\u6001\u7684\u4e8c\u7ef4\u5143\u80de\u81ea\u52a8\u673a\uff0c\u5305\u542b\u53ef\u4ee5\u5728\u8fde\u7eed\u65f6\u7a7a\u4e2d\u8fd0\u884c\u7684\u901a\u7528\u5c40\u90e8\u66f4\u65b0\u89c4\u5219\u3002\u4e0e\u79bb\u6563\u65f6\u95f4\u7684\u5143\u80de\u81ea\u52a8\u673a\u76f8\u6bd4\uff0cLenia\u7684\u6d8c\u73b0\u6a21\u5f0f\u66f4\u591a\u6837\uff0c\u66f4\u590d\u6742\u3002\u4f5c\u8005\u5c55\u73b0\u4e86\u4e0e\u73b0\u5b9e\u4e16\u754c\u7684\u5fae\u89c2\u751f\u7269\u76f8\u4f3c\u7684\u3001\u6709\u7740\u590d\u6742\u591a\u6837\u6027\u7684\u590d\u6742\u81ea\u4e3b\u6a21\u5f0f\uff0c\u5e76\u786e\u8ba4\u4e8618\u4e2a\u79d1\u7684400\u591a\u4e2a\u7269\u79cd\uff0c\u5176\u4e2d\u8bb8\u591a\u662f\u901a\u8fc7\u4e00\u4e2a\u6709\u4eba\u7c7b\u53c2\u4e0e\u7684\u4e92\u52a8\u6f14\u5316\u8ba1\u7b97\u754c\u9762\u53d1\u73b0\u7684\u3002Lenia\u5728\u4eba\u5de5\u751f\u547d\u5c4a\u5f88\u53d7\u6b22\u8fce\uff0c\u800c\u6211\u4eec\u4e5f\u5f00\u59cb\u770b\u5230\u4e00\u4e9b\u7814\u7a76\u91c7\u7528\u673a\u5668\u5b66\u4e60\u6765\u5e2e\u52a9\u5206\u6790Lenia\u6240\u80fd\u4ea7\u751f\u7684\u4eba\u5de5\u751f\u547d\u5f62\u5f0f\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u4e3a\u4e86\u5728Lenia\u4e2d\u53d1\u73b0\u66f4\u591a\u7684\u751f\u547d\u5f62\u5f0f\uff0cReinke\u7b49\u4eba[51]\u5c06\u5185\u5728\u52a8\u673a\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\uff08<\/span>\u6700\u521d\u4e3a\u673a\u5668\u4eba\u5b66\u4e2d\u4e3a\u9006\u5411\u6a21\u578b\u5b66\u4e60\u800c\u5f00\u53d1\uff09<\/span>\u7528\u4e8e\u81ea\u52a8\u53d1\u73b0Leniaz\u7b49\u9ad8\u7ef4\u590d\u6742\u52a8\u529b\u7cfb\u7edf\u4e2d\u7684\u5404\u79cd\u81ea\u7ec4\u7ec7\u6a21\u5f0f\uff0c\u5e76\u5c06\u5176\u4f5c\u4e3a\u5b9e\u9a8c\u548c\u8bc4\u4f30\u7684\u6846\u67b6\u3002\u4ed6\u4eec\u5728\u8be5\u65b9\u6cd5\u4e2d\uff0c\u628a\u5185\u5728\u52a8\u673a\u7684\u76ee\u6807\u63a2\u7d22\u4e0e\u5bf9\u76ee\u6807\u7a7a\u95f4<\/span>\uff08\u611f\u5174\u8da3\u7684\u6a21\u5f0f\u7279\u5f81\u7a7a\u95f4\uff09<\/span>\u7684\u65e0\u76d1\u7763\u5b66\u4e60\u7ed3\u5408\u8d77\u6765\u3002\u8fd9\u91cc\u7684\u65e0\u76d1\u7763\u5b66\u4e60\uff0c\u662f\u4f7f\u7528\u6df1\u5ea6\u81ea\u52a8\u7f16\u7801\u5668\u8fdb\u884c\u7684\u3002\u4ed6\u4eec\u7684\u7ed3\u679c\u8868\u660e\uff0c\u4f7f\u7528\u5185\u5728\u52a8\u673a\u7b97\u6cd5\uff0c\u5728\u4eceLenia\u5b66\u4e60\u7684\u65e0\u76d1\u7763\u8868\u5f81\u4e2d\u641c\u7d22\u65b0\u5947\u7684\u6a21\u5f0f\uff0c\u641c\u7d22\u7684\u6548\u7387\u548c\u5df2\u7ecf\u62e5\u6709\u4eba\u7c7b\u4e13\u5bb6\u8bc6\u522b\u7684\u6709\u8da3\u6a21\u5f0f\u6570\u636e\u5e93\u7684\u7cfb\u7edf\u76f8\u5dee\u4e0d\u591a\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u540e\u6765\uff0cEtcheverry\u7b49\u4eba[16]\u6307\u51fa\uff0c\u4e0d\u4f9d\u9760\u7528\u6237\u53cd\u9988\u7684\u81ea\u52a8\u7684\u591a\u6837\u6027\u9a71\u52a8\u7684\u53d1\u73b0\u7cfb\u7edf\uff0c\u6709\u7740\u6839\u672c\u7684\u5c40\u9650\u6027\u2014\u2014\u56e0\u4e3a\u6ca1\u6709\u4e00\u4e2a\u201c\u4ec0\u4e48\u662f\u6709\u8da3\u7684\u591a\u6837\u6027\u201d\u7684\u771f\u76f8<\/span>\uff08ground truth\uff09<\/span>\uff0c\u5b83\u5f3a\u70c8\u5730\u4f9d\u8d56\u4e8e\u6700\u7ec8\u89c2\u5bdf\u8005\u7684\u4e3b\u89c2\u610f\u89c1\u3002\u4f46\u4e0e\u6b64\u540c\u65f6\uff0c\u8ba9\u7528\u6237\u53c2\u4e0e\u5176\u4e2d\u5c31\u8fdd\u80cc\u4e86\u81ea\u52a8\u53d1\u73b0\u7684\u76ee\u7684\u3002\u4e3a\u4e86\u89e3\u51b3\u8fd9\u4e2a\u95ee\u9898\uff0c\u4ed6\u4eec\u5f15\u5165\u4e86\u4e00\u4e2a\u6a21\u5757\u5316\u67b6\u6784\uff0c\u53ef\u4ee5\u5bf9\u591a\u6837\u6027\u8868\u5f81\u7684\u5c42\u6b21\u8fdb\u884c\u65e0\u76d1\u7763\u5b66\u4e60\uff0c\u7406\u8bba\u4e0a\u80fd\u591f\u6355\u6349\u5230\u5404\u79cd\u4e0d\u540c\u7684\u4eba\u7c7b\u4e3b\u89c2\u504f\u597d\uff0c\u540c\u65f6\u4ecd\u7136\u91c7\u7528\u5185\u5728\u52a8\u673a\u7684\u76ee\u6807\u63a2\u7d22\u7b97\u6cd5\uff0c\u5982Etcheverry\u7b49\u4eba\u63d0\u51fa\u7684\u7b97\u6cd5\u3002\u5728Lenia\u4e0a\u6d4b\u8bd5\u8fd9\u4e2a\u65b9\u6cd5\uff0c\u5f97\u5230\u7684\u662f\u4e00\u4e2a\u7c7b\u4f3c\u4e8e\u52a9\u624b\u7684\u7cfb\u7edf\uff0c\u53ea\u7528\u5f88\u5c11\u7684\u53cd\u9988\u5c31\u80fd\u6709\u6548\u5730\u4f7f\u5176\u591a\u6837\u6027\u641c\u7d22\u9002\u5e94\u7528\u6237\u7684\u504f\u597d\u3002<\/span><\/section>\n
 <\/span><\/section>\n
<\/section>\n

\u56fe11. \u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u5df2\u7ecf\u88ab\u7528\u6765\u5728\u8fde\u7eed\u7684\u5143\u80de\u81ea\u52a8\u673a\u7cfb\u7edf\uff08\u5982Lenia[6]\uff09\u4e2d\u81ea\u52a8\u53d1\u73b0\u4eba\u5de5\u751f\u547d\u4f53[16,51]\u3002\u6700\u8fd1\u7684\u7814\u7a76[16]\u4e0d\u4ec5\u80fd\u81ea\u52a8\u53d1\u73b0\u6709\u8da3\u7684\u6a21\u5f0f\uff0c\u800c\u4e14\u8fd8\u80fd\u5c06\u7528\u6237\u5bf9\u7279\u5b9a\u7c7b\u578b\u7684\u6709\u8da3\u6027\u7684\u504f\u597d\u7eb3\u5165\u5176\u641c\u7d22\u8fc7\u7a0b\u3002\u8fd9\u6837\uff0c\u5b83\u5c31\u53ef\u4ee5\u5728Lenia\u4e2d\u5bfb\u627e\u5c40\u90e8\u7a7a\u95f4\u91cc\u7684\u6a21\u5f0f\uff0c\u6216\u7c7b\u56fe\u7075\u7684\u751f\u547d\u5f62\u5f0f\u3002<\/span><\/p>\n

 <\/span><\/section>\n

\n

<\/span><\/section>\n<\/h3>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

\u4e94\u3001\u7ed3\u8bba<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u5728\u8fd9\u7bc7\u7efc\u8ff0\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u7b80\u8981\u4ecb\u7ecd\u4e86\u5386\u53f2\u80cc\u666f\uff0c\u63cf\u8ff0\u4e86\u795e\u7ecf\u7f51\u7edc\u548c\u96c6\u4f53\u667a\u80fd\u7814\u7a76\u76f8\u4e92\u4ea4\u7ec7\u7684\u53d1\u5c55\u3002\u8fd9\u4e24\u4e2a\u7814\u7a76\u9886\u57df\u7684\u8bde\u751f\u65f6\u95f4\u5927\u81f4\u76f8\u540c\uff0c\u5728\u5386\u53f2\u4e0a\u7684\u5174\u8870\u4e5f\u5b58\u5728\u7740\u4e00\u4e9b\u6b63\u76f8\u5173\u7684\u5173\u7cfb\u3002\u8fd9\u5e76\u4e0d\u662f\u5de7\u5408\uff0c\u56e0\u4e3a\u8fd9\u4e24\u4e2a\u9886\u57df\u4e2d\u4e00\u4e2a\u7684\u8fdb\u6b65\u548c\u7a81\u7834\uff0c\u901a\u5e38\u53ef\u4ee5\u4ea7\u751f\u65b0\u60f3\u6cd5\uff0c\u6216\u4e3a\u53e6\u4e00\u4e2a\u9886\u57df\u8865\u5145\u89e3\u51b3\u65b9\u6848\u3002\u4f8b\u5982\uff0c\u5c06\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u548c\u76f8\u5173\u8bad\u7ec3\u7b97\u6cd5\u5f15\u5165\u5143\u80de\u81ea\u52a8\u673a\uff0c\u6211\u4eec\u80fd\u591f\u5f00\u53d1\u51fa\u6297\u566a\u97f3\u548c\u5177\u6709\u201c\u81ea\u6211\u4fee\u590d\u201d\u7279\u6027\u7684\u56fe\u50cf\u751f\u6210\u7b97\u6cd5\u3002\u8fd9\u7bc7\u7efc\u8ff0\u63a2\u8ba8\u4e86\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u4e2d\u7684\u51e0\u9879\u5de5\u4f5c\uff0c\u8fd9\u51e0\u9879\u5de5\u4f5c\u4e5f\u53d7\u5230\u4e86\u96c6\u4f53\u667a\u80fd\u9886\u57df\u4e2d\u4e00\u4e9b\u6982\u5ff5\u7684\u542f\u53d1\u3002\u5728\u5b8f\u89c2\u5c42\u9762\u4e0a\uff0c\u591a\u667a\u80fd\u4f53\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u96c6\u4f53\u667a\u80fd\u5e26\u6765\u4e86\u53ef\u4ee5\u901a\u8fc7\u96c6\u4f53\u81ea\u5bf9\u5f08\u6765\u8d85\u8d8a\u4eba\u7c7b\u8868\u73b0\u7684\u6709\u8da3\u6a21\u578b\uff0c\u4e5f\u5e26\u6765\u4e86\u53bb\u4e2d\u5fc3\u5316\u7684\u81ea\u7ec4\u7ec7\u7684\u673a\u5668\u4eba\u63a7\u5236\u5668\uff1b\u5728\u5fae\u89c2\u5c42\u9762\u4e0a\uff0c\u4e00\u4e9b\u5148\u8fdb\u7684\u65b9\u6cd5\u4e5f\u5d4c\u5165\u4e86\u96c6\u4f53\u667a\u80fd\uff0c\u7528\u6df1\u5ea6\u6a21\u578b\u5728\u66f4\u7ec6\u7684\u9897\u7c92\u5ea6\u4e0a\u6a21\u62df\u5404\u4e2a\u795e\u7ecf\u5143\u3001\u7a81\u89e6\u6216\u5176\u5b83\u5bf9\u8c61\u3002<\/span><\/section>\n
 <\/span><\/section>\n
\u7eb5\u89c2\u5b83\u4eec\u5404\u81ea\u7684\u53d1\u5c55\u8f68\u8ff9\uff0c\u6df1\u5ea6\u5b66\u4e60\u5728\u5f00\u53d1\u65b0\u578b\u67b6\u6784\u548c\u8bad\u7ec3\u7b97\u6cd5\u65b9\u9762\u53d6\u5f97\u4e86\u663e\u8457\u7684\u6210\u5c31\uff0c\u4ece\u800c\u5b9e\u73b0\u4e86\u9ad8\u6548\u7684\u5b66\u4e60\u548c\u66f4\u597d\u7684\u6027\u80fd\uff0c\u800c\u96c6\u4f53\u667a\u80fd\u5219\u66f4\u6ce8\u91cd\u95ee\u9898\u7684\u8868\u8ff0\u548c\u673a\u5236\uff0c\u4ee5\u6b64\u4fc3\u8fdb\u65b0\u9896\u7684\u8868\u73b0\u6216\u6bd4\u7b80\u5355\u5730\u805a\u96c6\u5404\u4e2a\u7ed3\u679c\u66f4\u597d\u7684\u7ed3\u679c\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u6709\u7406\u7531\u8ba4\u4e3a\uff0c\u8fd9\u4e24\u4e2a\u9886\u57df\u5904\u4e8e\u4e0d\u540c\u7684\u62bd\u8c61\u5c42\u6b21\uff0c\u53ef\u4ee5\u4e92\u76f8\u8865\u5145\u3002\u6211\u4eec\u76f8\u4fe1\uff0c\u8fd9\u79cd\u643a\u624b\u5e76\u8fdb\u7684\u5171\u540c\u53d1\u5c55\u5c06\u7ee7\u7eed\u4e0b\u53bb\u3002\u6709\u5e0c\u671b\u7684\u672a\u6765\u53d1\u5c55\u65b9\u5411\u53ef\u80fd\u5305\u62ec\uff1a\u5c06\u6bcf\u4e2a\u5355\u72ec\u7684\u795e\u7ecf\u5143\u6216\u8005\u7a81\u89e6\u6a21\u62df\u4e3a\u6574\u4e2a\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\uff0c\u4ee5\u53ca\u5f00\u53d1\u80fd\u5b66\u4e60\u7fa4\u4f53\u4e4b\u95f4\u76f8\u4e92\u4f5c\u7528\u7684\u7b97\u6cd5\uff0c\u6765\u590d\u73b0\u771f\u5b9e\u5927\u8111\u7684\u884c\u4e3a\u3002\u6b64\u5916\uff0c\u96c6\u4f53\u667a\u80fd\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u8fd9\u79cd\u7ed3\u5408\uff0c\u4e5f\u8bb8\u80fd\u4f7f\u6a21\u62df\u7684\u4eba\u5de5\u6587\u660e\u53cd\u6620\u51fa\u6211\u4eec\u4eba\u7c7b\u6587\u660e\u7684\u67d0\u4e9b\u65b9\u9762\uff0c\u8574\u542b\u7740\u9020\u5c31\u6211\u4eec\u96c6\u4f53\u667a\u80fd\u7684\u6240\u6709\u590d\u6742\u6027\u3002<\/span><\/section>\n
 <\/span><\/section>\n

<\/span><\/section>\n
\n
\n
\n

\u53c2\u8003\u6587\u732e<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n

\n
\n
\n
\n


<\/p>\n

    \n
  1. \n
    Baker B, Kanitscheider I, Markov T, Wu Y, Powell G, McGrew B and Mordatch I (2019) Emergent tool use from multi-agent autocurricula. arXiv preprint arXiv:1909.07528 .<\/section>\n<\/li>\n
  2. \n
    Bansal T, Pachocki J, Sidor S, Sutskever I and Mordatch I (2017) Emergent complexity via multi-agent competition. arXiv preprint arXiv:1710.03748 .<\/section>\n<\/li>\n
  3. \n
    Bhatia J, Jackson H, Tian Y, Xu J and Matusik W (2021) Evolution gym: A large-scale benchmark for evolving soft robots. In: Advances in Neural Information Processing Systems. Curran Associates, Inc. URL https:\/\/sites.google.com\/corp\/view\/evolution-gym-benchmark\/.<\/section>\n<\/li>\n
  4. \n
    Brockman G, Cheung V, Pettersson L, Schneider J, Schulman J, Tang J and Zaremba W (2016) Openai gym. arXiv preprint arXiv:1606.01540 .<\/section>\n<\/li>\n
  5. \n
    Brown TB, Mann B, Ryder N, Subbiah M, Kaplan J, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A et al. (2020) Language models are few-shot learners. arXiv preprint arXiv:2005.14165 .<\/section>\n<\/li>\n
  6. \n
    Chan BWC (2019) Lenia: Biology of artificial life. Complex Systems 28(3): 251\u2013286. DOI:10.25088\/ complexsystems.28.3.251. URL http:\/\/dx.doi.org\/10.25088\/complexsystems.28.3.251.<\/section>\n<\/li>\n
  7. \n
    Chan BWC (2020) Lenia and expanded universe. In: Proceedings of the ALIFE 2020: The 2020 Conference on Artificial Life. pp. 221\u2013229. DOI:10.1162\/isal a 00297. URL https:\/\/doi.org\/10.1162\/isal_ a_00297.<\/section>\n<\/li>\n
  8. \n
    Cheney N, MacCurdy R, Clune J and Lipson H (2014) Unshackling evolution: evolving soft robots with multiple materials and a powerful generative encoding. ACM SIGEVOlution 7(1): 11\u201323.<\/section>\n<\/li>\n
  9. \n
    Chollet F et al. (2015) keras.<\/section>\n<\/li>\n
  10. \n
    Chua LO and Roska T (2002) Cellular neural networks and visual computing: foundations and applications. Cambridge university press.<\/section>\n<\/li>\n
  11. \n
    Chua LO and Yang L (1988) Cellular neural networks: Applications. IEEE Transactions on circuits and systems 35(10): 1273\u20131290.<\/section>\n<\/li>\n
  12. \n
    Chua LO and Yang L (1988) Cellular neural networks: Theory. IEEE Transactions on circuits and systems 35(10): 1257\u20131272.<\/section>\n<\/li>\n
  13. \n
    Cisneros H, Sivic J and Mikolov T (2019) Evolving structures in complex systems. arXiv preprint arXiv:1911.01086 .<\/section>\n<\/li>\n
  14. \n
    Conway J et al. (1970) The game of life. Scientific American 223(4): 4.<\/section>\n<\/li>\n
  15. \n
    Daigavane A, Ravindran B and Aggarwal G (2021) Understanding convolutions on graphs. Distill DOI: 10.23915\/distill.00032. Https:\/\/distill.pub\/2021\/understanding-gnns.<\/section>\n<\/li>\n
  16. \n
    Deng J, Dong W, Socher R, Li LJ, Li K and Fei-Fei L (2009) Imagenet: A large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition. Ieee, pp. 248\u2013255.<\/section>\n<\/li>\n
  17. \n
    Etcheverry M, Moulin-Frier C and Oudeyer PY (2020) Hierarchically organized latent modules for exploratory search in morphogenetic systems. In: Advances in Neural Information Processing Systems, volume 33. Curran Associates, Inc., pp. 4846\u20134859. URL https:\/\/proceedings.neurips.cc\/paper\/2020\/file\/ 33a5435d4f945aa6154b31a73bab3b73-Paper.pdf.<\/section>\n<\/li>\n
  18. \n
    Foerster JN, Assael YM, De Freitas N and Whiteson S (2016) Learning to communicate with deep multi-agent reinforcement learning. arXiv preprint arXiv:1605.06676 .<\/section>\n<\/li>\n
  19. \n
    Freeman CD, Metz L and Ha D (2019) Learning to predict without looking ahead: World models without forward prediction URL https:\/\/learningtopredict.github.io.<\/section>\n<\/li>\n
  20. \n
    Gilpin W (2019) Cellular automata as convolutional neural networks. Physical Review E 100(3): 032402.<\/section>\n<\/li>\n
  21. \n
    GoraS L, Chua LO and Leenaerts D (1995) Turing patterns in cnns. i. once over lightly. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 42(10): 602\u2013611.<\/section>\n<\/li>\n
  22. \n
    Grattarola D, Livi L and Alippi C (2021) Learning graph cellular automata.<\/section>\n<\/li>\n
  23. \n
    Ha D (2018) Reinforcement learning for improving agent design URL https:\/\/designrl.github.io.<\/section>\n<\/li>\n
  24. \n
    Ha D (2020) Slime volleyball gym environment. https:\/\/github.com\/hardmaru\/ slimevolleygym.<\/section>\n<\/li>\n
  25. \n
    Hamann H (2018) Swarm robotics: A formal approach. Springer.<\/section>\n<\/li>\n
  26. \n
    He K, Zhang X, Ren S and Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 770\u2013778.<\/section>\n<\/li>\n
  27. \n
    Heiden E, Millard D, Coumans E, Sheng Y and Sukhatme GS (2021) NeuralSim: Augmenting differentiable simulators with neural networks. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). URL https:\/\/github.com\/google-research\/ tiny-differentiable-simulator.<\/section>\n<\/li>\n
  28. \n
    Hill A, Raffin A, Ernestus M, Gleave A, Kanervisto A, Traore R, Dhariwal P, Hesse C, Klimov O, Nichol A et al. (2018) Stable baselines.<\/section>\n<\/li>\n
  29. \n
    Hooker S (2020) The hardware lottery. arXiv preprint arXiv:2009.06489 URL https:\/\/ hardwarelottery.github.io\/.<\/section>\n<\/li>\n
  30. \n
    Horibe K, Walker K and Risi S (2021) Regenerating soft robots through neural cellular automata. In: EuroGP. pp. 36\u201350.<\/section>\n<\/li>\n
  31. \n
    Huang W, Mordatch I and Pathak D (2020) One policy to control them all: Shared modular policies for agentagnostic control. In: International Conference on Machine Learning. PMLR, pp. 4455\u20134464.<\/section>\n<\/li>\n
  32. \n
    Jaderberg M, Czarnecki WM, Dunning I, Marris L, Lever G, Castaneda AG, Beattie C, Rabinowitz NC, Morcos AS, Ruderman A et al. (2019) Human-level performance in 3d multiplayer games with populationbased reinforcement learning. Science 364(6443): 859\u2013865.<\/section>\n<\/li>\n
  33. \n
    Joachimczak M, Suzuki R and Arita T (2016) Artificial metamorphosis: Evolutionary design of transforming, soft-bodied robots. Artificial life 22(3): 271\u2013298.<\/section>\n<\/li>\n
  34. \n
    Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, Tunyasuvunakool K, Bates R, Z\u02c7\u00b4\u0131dek A, Potapenko A et al. (2021) Highly accurate protein structure prediction with alphafold. Nature 596(7873): 583\u2013 589.<\/section>\n<\/li>\n
  35. \n
    Kirsch L and Schmidhuber J (2020) Meta learning backpropagation and improving it. arXiv preprint arXiv:2012.14905 .<\/section>\n<\/li>\n
  36. \n
    Kozek T, Roska T and Chua LO (1993) Genetic algorithm for cnn template learning. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 40(6): 392\u2013402.<\/section>\n<\/li>\n
  37. \n
    Krizhevsky A, Sutskever I and Hinton GE (2012) Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems 25: 1097\u20131105.<\/section>\n<\/li>\n
  38. \n
    Liu S, Lever G, Merel J, Tunyasuvunakool S, Heess N and Graepel T (2019) Emergent coordination through competition. arXiv preprint arXiv:1902.07151 .<\/section>\n<\/li>\n
  39. \n
    Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, Graves A, Riedmiller M, Fidjeland AK, Ostrovski G et al. (2015) Human-level control through deep reinforcement learning. nature 518(7540): 529\u2013533.<\/section>\n<\/li>\n
  40. \n
    Mordvintsev A, Randazzo E, Niklasson E and Levin M (2020) Growing neural cellular automata. Distill DOI: 10.23915\/distill.00023. URL https:\/\/distill.pub\/2020\/growing-ca.<\/section>\n<\/li>\n
  41. \n
    Nagy Z, Voroshazi Z and Szolgay P (2006) A real-time mammalian retina model implementation on fpga. In: 2006 10th International Workshop on Cellular Neural Networks and Their Applications. IEEE, pp. 1\u20131.<\/section>\n<\/li>\n
  42. \n
    Ohsawa S, Akuzawa K, Matsushima T, Bezerra G, Iwasawa Y, Kajino H, Takenaka S and Matsuo Y (2018) Neuron as an agent. URL https:\/\/openreview.net\/forum?id=BkfEzz-0-.<\/section>\n<\/li>\n
  43. \n
    OroojlooyJadid A and Hajinezhad D (2019) A review of cooperative multi-agent deep reinforcement learning. arXiv preprint arXiv:1908.03963 .<\/section>\n<\/li>\n
  44. \n
    Ott J (2020) Giving up control: Neurons as reinforcement learning agents. arXiv preprint arXiv:2003.11642 .<\/section>\n<\/li>\n
  45. \n
    Pandarinath C, O\u2019Shea DJ, Collins J, Jozefowicz R, Stavisky SD, Kao JC, Trautmann EM, Kaufman MT, Ryu SI, Hochberg LR et al. (2018) Inferring single-trial neural population dynamics using sequential auto-encoders. Nature methods 15(10): 805\u2013815.<\/section>\n<\/li>\n
  46. \n
    Pathak D, Lu C, Darrell T, Isola P and Efros AA (2019) Learning to control self-assembling morphologies: a study of generalization via modularity. arXiv preprint arXiv:1902.05546 .<\/section>\n<\/li>\n
  47. \n
    Peng Z, Hui KM, Liu C, Zhou B et al. (2021) Learning to simulate self-driven particles system with coordinated policy optimization. Advances in Neural Information Processing Systems 34.<\/section>\n<\/li>\n
  48. \n
    Qin Y, Feng M, Lu H and Cottrell GW (2018) Hierarchical cellular automata for visual saliency. International Journal of Computer Vision 126(7): 751\u2013770.<\/section>\n<\/li>\n
  49. \n
    Qu X, Sun Z, Ong YS, Gupta A and Wei P (2020) Minimalistic attacks: How little it takes to fool deep reinforcement learning policies. IEEE Transactions on Cognitive and Developmental Systems .<\/section>\n<\/li>\n
  50. \n
    Radford A, Kim JW, Hallacy C, Ramesh A, Goh G, Agarwal S, Sastry G, Askell A, Mishkin P, Clark J et al. (2021) Learning transferable visual models from natural language supervision. arXiv preprint arXiv:2103.00020 .<\/section>\n<\/li>\n
  51. \n
    Radford A, Narasimhan K, Salimans T and Sutskever I (2018) Improving language understanding by generative pre-training .<\/section>\n<\/li>\n
  52. \n
    Radford A, Wu J, Child R, Luan D, Amodei D, Sutskever I et al. (2019) Language models are unsupervised multitask learners. OpenAI blog 1(8): 9.<\/section>\n<\/li>\n
  53. \n
    Randazzo E, Mordvintsev A, Niklasson E, Levin M and Greydanus S (2020) Self-classifying mnist digits. Distill DOI:10.23915\/distill.00027.002. URL https:\/\/distill.pub\/2020\/selforg\/mnist.<\/section>\n<\/li>\n
  54. \n
    Reinke C, Etcheverry M and Oudeyer PY (2020) Intrinsically motivated discovery of diverse patterns in self-organizing systems. In: International Conference on Learning Representations. URL https:\/\/ openreview.net\/forum?id=rkg6sJHYDr.<\/section>\n<\/li>\n
  55. \n
    Resnick C, Eldridge W, Ha D, Britz D, Foerster J, Togelius J, Cho K and Bruna J (2018) Pommerman: A multi-agent playground. arXiv preprint arXiv:1809.07124 .<\/section>\n<\/li>\n
  56. \n
    Rolnick D, Donti PL, Kaack LH, Kochanski K, Lacoste A, Sankaran K, Ross AS, Milojevic-Dupont N, Jaques N, Waldman-Brown A et al. (2019) Tackling climate change with machine learning. arXiv preprint arXiv:1906.05433 .<\/section>\n<\/li>\n
  57. \n
    Rubenstein M, Cornejo A and Nagpal R (2014) Programmable self-assembly in a thousand-robot swarm. Science 345(6198): 795\u2013799.<\/section>\n<\/li>\n
  58. \n
    Rudin N, Hoeller D, Reist P and Hutter M (2021) Learning to walk in minutes using massively parallel deep reinforcement learning. arXiv preprint arXiv:2109.11978 .<\/section>\n<\/li>\n
  59. \n
    Sanchez-Lengeling B, Reif E, Pearce A and Wiltschko AB (2021) A gentle introduction to graph neural networks. Distill 6(9): e33.<\/section>\n<\/li>\n
  60. \n
    Sandler M, Vladymyrov M, Zhmoginov A, Miller N, Madams T, Jackson A and Arcas BAY (2021) Metalearning bidirectional update rules. In: International Conference on Machine Learning. PMLR, pp. 9288\u20139300<\/section>\n<\/li>\n
  61. \n
    Sandler M, Zhmoginov A, Luo L, Mordvintsev A, Randazzo E et al. (2020) Image segmentation via cellular automata. arXiv preprint arXiv:2008.04965 .<\/section>\n<\/li>\n
  62. \n
    Schmidhuber J (2014) Who invented backpropagation? More[DL2] .<\/section>\n<\/li>\n
  63. \n
    Schoenholz S and Cubuk ED (2020) Jax md: a framework for differentiable physics. Advances in Neural Information Processing Systems 33.<\/section>\n<\/li>\n
  64. \n
    Senior AW, Evans R, Jumper J, Kirkpatrick J, Sifre L, Green T, Qin C, Z\u02c7\u00b4\u0131dek A, Nelson AW, Bridgland A et al. (2020) Improved protein structure prediction using potentials from deep learning. Nature 577(7792): 706\u2013710.<\/section>\n<\/li>\n
  65. \n
    Silver D, Huang A, Maddison CJ, Guez A, Sifre L, Van Den Driessche G, Schrittwieser J, Antonoglou I, Panneershelvam V, Lanctot M et al. (2016) Mastering the game of go with deep neural networks and tree search. nature 529(7587): 484\u2013489.<\/section>\n<\/li>\n
  66. \n
    Simonyan K and Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 .<\/section>\n<\/li>\n
  67. \n
    Stoy K, Brandt D, Christensen DJ and Brandt D (2010) Self-reconfigurable robots: an introduction .<\/section>\n<\/li>\n
  68. \n
    Suarez J, Du Y, Isola P and Mordatch I (2019) Neural mmo: A massively multiagent game environment for training and evaluating intelligent agents. arXiv preprint arXiv:1903.00784 .<\/section>\n<\/li>\n
  69. \n
    Suarez J, Du Y, Zhu C, Mordatch I and Isola P (2021) The neural mmo platform for massively multiagent research. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track. URL https:\/\/openreview.net\/forum?id=J0d-I8yFtP.<\/section>\n<\/li>\n
  70. \n
    Sudhakaran S, Grbic D, Li S, Katona A, Najarro E, Glanois C and Risi S (2021) Growing 3d artefacts and functional machines with neural cellular automata. arXiv preprint arXiv:2103.08737 .<\/section>\n<\/li>\n
  71. \n
    Tang Y and Ha D (2021) The sensory neuron as a transformer: Permutation-invariant neural networks for reinforcement learning. In: Thirty-Fifth Conference on Neural Information Processing Systems. URL https: \/\/openreview.net\/forum?id=wtLW-Amuds. https:\/\/attentionneuron.github.io.<\/section>\n<\/li>\n
  72. \n
    Tang Y, Nguyen D and Ha D (2020) Neuroevolution of self-interpretable agents. In: Proceedings of the Genetic and Evolutionary Computation Conference. URL https:\/\/attentionagent.github.io.<\/section>\n<\/li>\n
  73. \n
    Terry JK, Black B, Jayakumar M, Hari A, Sullivan R, Santos L, Dieffendahl C, Williams NL, Lokesh Y, Horsch C et al. (2020) Pettingzoo: Gym for multi-agent reinforcement learning. arXiv preprint arXiv:2009.14471 .<\/section>\n<\/li>\n
  74. \n
    Vinyals O, Babuschkin I, Czarnecki WM, Mathieu M, Dudzik A, Chung J, Choi DH, Powell R, Ewalds T, Georgiev P et al. (2019) Grandmaster level in starcraft ii using multi-agent reinforcement learning. Nature 575(7782): 350\u2013354.<\/section>\n<\/li>\n
  75. \n
    Wang T, Liao R, Ba J and Fidler S (2018) Nervenet: Learning structured policy with graph neural networks. In: International Conference on Learning Representations.<\/section>\n<\/li>\n
  76. \n
    Wolfram S (2002) A new kind of science, volume 5. Wolfram media Champaign, IL.<\/section>\n<\/li>\n
  77. \n
    Wu Z, Pan S, Chen F, Long G, Zhang C and Philip SY (2020) A comprehensive survey on graph neural networks. IEEE transactions on neural networks and learning systems 32(1): 4\u201324.<\/section>\n<\/li>\n
  78. \n
    Zenil H (2009) Compression-based investigation of the dynamical properties of cellular automata and other systems. arXiv preprint arXiv:0910.4042 .<\/section>\n<\/li>\n
  79. \n
    Zhang D, Choi C, Kim J and Kim YM (2021) Learning to generate 3d shapes with generative cellular automata. In: International Conference on Learning Representations. URL https:\/\/openreview.net\/forum? id=rABUmU3ulQh.<\/section>\n<\/li>\n
  80. \n
    Zheng L, Yang J, Cai H, Zhou M, Zhang W, Wang J and Yu Y (2018) Magent: A many-agent reinforcement learning platform for artificial collective intelligence. In: Proceedings of the AAAI Conference on Artificial Intelligence, volume 32<\/section>\n<\/li>\n<\/ol>\n


    <\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

    \n
    \n

    \u53c2\u8003\u6587\u732e\u53ef\u4e0a\u4e0b\u6ed1\u52a8<\/strong>\u67e5\u770b<\/p>\n<\/section>\n<\/section>\n


    <\/span>
    <\/p>\n


    <\/p>\n

    \n
    \n
    \n
    \n

    \u590d\u6742\u79d1\u5b66\u6700\u65b0\u8bba\u6587<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

    \n


    <\/p>\n<\/section>\n

    \u96c6\u667a\u6591\u56fe\u9876\u520a\u8bba\u6587\u901f\u9012\u680f\u76ee\u4e0a\u7ebf\u4ee5\u6765\uff0c\u6301\u7eed\u6536\u5f55\u6765\u81eaNature\u3001Science<\/span>\u7b49\u9876\u520a\u7684\u6700\u65b0\u8bba\u6587\uff0c\u8ffd\u8e2a\u590d\u6742\u7cfb\u7edf\u3001\u7f51\u7edc\u79d1\u5b66\u3001\u8ba1\u7b97\u793e\u4f1a\u79d1\u5b66\u7b49\u9886\u57df\u7684\u524d\u6cbf\u8fdb\u5c55\u3002\u73b0\u5728\u6b63\u5f0f\u63a8\u51fa\u8ba2\u9605\u529f\u80fd\uff0c\u6bcf\u5468\u901a\u8fc7\u5fae\u4fe1\u670d\u52a1\u53f7\u300c\u96c6\u667a\u6591\u56fe\u300d\u63a8\u9001\u8bba\u6587\u4fe1\u606f\u3002\u626b\u63cf\u4e0b\u65b9\u4e8c\u7ef4\u7801\u5373\u53ef\u4e00\u952e\u8ba2\u9605\uff1a<\/span>
    <\/p>\n

    <\/p>\n

    \n


    <\/p>\n<\/section>\n


    <\/p>\n

    \n

    \u63a8\u8350\u9605\u8bfb<\/span><\/strong><\/strong><\/p>\n