{"id":8362,"date":"2016-12-10T01:00:00","date_gmt":"2016-12-09T17:00:00","guid":{"rendered":"http:\/\/swarma.org\/%swarma-paper%\/"},"modified":"2018-12-06T08:31:54","modified_gmt":"2018-12-06T00:31:54","slug":"%e5%9f%ba%e4%ba%8e%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c%e7%9a%84%e6%99%ba%e8%83%bd%e6%8e%a7%e5%88%b6%e6%8a%80%e6%9c%af%e5%8f%8a%e5%85%b6%e5%8f%91%e5%b1%95%e8%b6%8b%e5%8a%bf%e8%ae%b2%e5%ba%a7%e5%9b%9e","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=8362","title":{"rendered":"\u57fa\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u667a\u80fd\u63a7\u5236\u6280\u672f\u53ca\u5176\u53d1\u5c55\u8d8b\u52bf\u8bb2\u5ea7\u56de\u987e2 | \u539f\u521b\u7cbe\u9009"},"content":{"rendered":"
\n

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      <\/span>\u6628\u5929\u5f20\u6cfd\u946b\u5c0f\u5e05\u54e5\u7684\u7b14\u8bb0\u5206\u4eab\u4e00\u7ecf\u53d1\u51fa\uff0c\u83b7\u5f97\u4e86\u5927\u5bb6\u7684\u4e00\u81f4\u597d\u8bc4\uff01\u9664\u4e86\u5bf9\u7b14\u8bb0\u5e72\u8d27\u7684\u8d85\u9ad8\u8bc4\u4ef7\u5916\uff0c\u8fd8\u6709\u5c0f\u7c89\u4e1d\u7559\u8a00\u52fe\u642d~\u54c8\u54c8\u54c8\u54c8\u6211\u4eec\u5927\u96c6\u667a\u5c31\u662f\u8fd9\u4e48\u4eba\u624d\u6d4e\u6d4e\uff0c\u6c47\u805a\u82f1\u624d\uff01\uff08\u5982\u679c\u4f60\u4e5f\u89c9\u5f97\u81ea\u5df1\u5f88\u6709\u624d\uff0c\u5c31\u6765\u627e\u6211\u4eec\uff0c\u7ed9\u4f60\u821e\u53f0\uff01\uff09<\/span><\/p>\n

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\"\u96c6\u667a\"
  <\/span>\uff08\u5c0f\u7f16\u8bed\uff1a\u8981\u662f\u6709\u59b9\u5b50\u770b\u4e0a\u7684\u8bf7\u540e\u53f0\u7559\u8a00\uff0c\u5c0f\u7f16\u53ef\u4ee5\u7ed9\u4f60\u8054\u7cfb\u65b9\u5f0f\uff01\u5982\u679c\u662f\u6c49\u5b50\u7684\u8bdd\u5c31\u81ea\u5df1\u53bb\u6e05\u534e\u52fe\u642d\u5427~\u540e\u53f0\u7559\u8a00\u4e92\u52a8\u62bd\u53d6\u4e00\u540d\u5e78\u8fd0\u89c2\u4f17\u8d60\u9001\u96c6\u667a\u7cbe\u54c1T\u6064\u4e00\u4ef6~\u6709\u94b1\u4efb\u6027\uff09<\/span><\/p>\n

\n

\u5d14\u660a\u5929<\/span><\/strong>   \u6e05\u534e\u5927\u5b66\u7814\u7a76\u4eba\u5de5\u667a\u80fd\u7684\u5728\u8bfb\u7855\u58eb\uff0c\u4e00\u8fb9\u7814\u7a76\u673a\u5668\u7684\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\uff0c\u5f3a\u5316\u5b66\u4e60\uff0c\u4e00\u8fb9\u4e5f\u5173\u6ce8\u771f\u5b9e\u7684\u5927\u8111\u3002<\/span><\/span><\/p>\n<\/blockquote>\n


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\u524d\u8a00<\/span><\/strong><\/p>\n

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

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

1.<\/span><\/strong><\/span><\/h5>\n
\u667a\u80fd\u63a7\u5236\u4ecb\u7ecd<\/span><\/strong><\/span><\/o:p><\/h5>\n

<\/span><\/strong><\/span>\"\u96c6\u667a\"Figure 1. <\/span>\u6ce2\u58eb\u987f\u52a8\u529b\u7684\u673a\u5668\u4eba\u4eec<\/span><\/p>\n

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

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\"\u96c6\u667a\"Figure 2. \u53cd\u9988\u63a7\u5236<\/span>
<\/p>\n

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


<\/span><\/strong><\/span><\/h5>\n
2.<\/span><\/strong><\/span><\/h5>\n
\u795e\u7ecf\u63a7\u5236\u65b0\u65b9\u6cd5<\/span><\/strong><\/span><\/h5>\n

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

2.1\u4ec0\u4e48\u662f\u795e\u7ecf\u7f51\u7edc\u63a7\u5236<\/span><\/strong><\/p>\n

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\"\u96c6\u667a\"
Figure 4. \u795e\u7ecf\u7f51\u7edc\u63a7\u5236\uff0c\u6ce8\u610f\u4e0eFigure2\u7684\u5dee\u522b<\/span><\/p>\n

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2.2\u7ebf\u4e0a\u81ea\u9002\u5e94\u5b66\u4e60<\/span><\/strong><\/p>\n

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\"\u96c6\u667a\"
<\/span>Figure 5. \u7ebf\u4e0a\u81ea\u9002\u5e94\u5b66\u4e60<\/span><\/p>\n

\u8fd9\u4e00\u70b9\u5c31\u533a\u522b\u4e8eMachine Learning\u4e2d\u8bad\u7ec3\u96c6\uff0c\u6d4b\u8bd5\u96c6\u7684\u8bbe\u7f6e\uff0c\u4ee5\u53ca\u8bad\u7ec3\u96c6\u6d4b\u8bd5\u96c6\u540c\u5206\u5e03\u7684\u5047\u8bbe\u3002\u8bb2\u5ea7\u4e2d\u5728\u8fd9\u91cc\u653e\u4e86\u5f88\u5f62\u8c61\u7684\u56fe\uff0c\u636e\u8bf4\u6765\u81ea\u63a7\u5236\u9886\u57df\u5927\u725bS.S.Ge\u66fe\u7ecf\u7684slides\uff1a<\/span><\/p>\n

\"\u96c6\u667a\"Figure 6. \u9a91\u6469\u6258\u8f66\u4e2d\u7684\u81ea\u9002\u5e94\u63a7\u5236<\/span><\/p>\n

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<\/span>Figure 7. \u5de6\uff1a\u884c\u4e3a\u5b66\u4e2d\u7684\u5956\u52b1\u673a\u5236\u3002<\/span><\/p>\n

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

3.<\/span><\/strong><\/h5>\n
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1.\u4e0e\u6df1\u5ea6\u7f51\u7edc\u7684\u89c4\u6a21\u5dee\u522b<\/span><\/strong><\/p>\n

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2.\u4e0e\u5f3a\u5316\u5b66\u4e60\u7684\u8054\u7cfb<\/span><\/strong><\/p>\n

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3.\u4e0e\u5927\u8111\u5956\u52b1\u673a\u5236\u7684\u8054\u7cfb<\/span><\/strong><\/p>\n

\"\u96c6\u667a\"
<\/p>\n

Figure 8. \u7ecf\u8fc7\u8bad\u7ec3\u4ea7\u751f\u7684\u591a\u5df4\u80fa\u80fd\u795e\u7ecf\u5143\u53ef\u4ee5\u5728reward\u53d1\u751f\u524d\u8fdb\u884c\u51c6\u786e\u9884\u6d4b\u3002<\/span><\/p>\n

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 <\/span><\/p>\n

4.<\/span><\/strong><\/span><\/p>\n

\u7ed3\u6784\u52a8\u6001\u7684\u795e\u7ecf\u7f51\u7edc<\/span><\/strong><\/span><\/p>\n

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

Reference:<\/span><\/strong><\/p>\n

[1] He K, Zhang X, Ren S, et al. Deep residual learning for image recognition[J]. arXiv preprint arXiv:1512.03385, 2015.<\/span><\/p>\n

[2] Sutton R S, Barto A G. Reinforcement learning: An introduction[M]. Cambridge: MIT press, 1998.<\/span><\/p>\n

[3] Schultz W, Dayan P, Montague P. A neural substrate of prediction and reward[J], Science, 1997, 275:1593-1599.<\/span><\/p>\n


<\/p>\n

– NOT END –<\/span><\/p>\n

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\u79d1\u666e\u4e00\u4e0b\u5973\u795e\u7684\u7fa4\uff01<\/span><\/strong><\/span><\/p>\n

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1\u3001\u626b\u63cf\u4e8c\u7ef4\u7801\u6216\u8005\u70b9\u51fb\u9605\u8bfb\u539f\u6587\u586b\u5199\u9ea6\u514b\u8868\u5355\u3002<\/span><\/p>\n

\"\u96c6\u667a\"
<\/span><\/p>\n

2\u3001\u901a\u8fc7\u96c6\u667a\u76f8\u5173\u4eba\u5458\u7684\u597d\u53cb\u7533\u8bf7\u5373\u53ef\u5165\u7fa4\u3002<\/span><\/p>\n

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\"\u96c6\u667a\"
<\/span><\/p>\n

– END –<\/span><\/p>\n

\n

\u96c6\u667a\u4ff1\u4e50\u90e8<\/span><\/strong><\/p>\n

\u82f1\u6587\u540d\uff1a Swarm Agents Club \uff0c\u7b80\u79f0\u201c SA Club \u201d\uff0c\u6210\u7acb\u4e8e 2008 \u5e74 \uff0c \u662f\u4e00\u4e2a\u4ece\u4e8b\u5b66\u672f\u7814\u7a76\u3001\u4eab\u53d7\u79d1\u5b66\u4e50\u8da3\u7684\u63a2\u7d22\u8005\u7684\u56e2\u4f53 \u3002\u5b83\u5021\u5bfc\u4ee5\u5e73\u7b49\u5f00\u653e\u7684\u6001\u5ea6\u3001\u79d1\u5b66\u5b9e\u8bc1\u7684\u7cbe\u795e\uff0c\u8fdb\u884c\u8de8\u5b66\u79d1\u7684\u7814\u7a76\u4e0e\u4ea4\u6d41\uff0c\u529b\u56fe\u642d\u5efa\u4e00\u4e2a\u4e2d\u56fd\u7684 \u201c \u6ca1\u6709\u56f4\u5899\u7684\u7814\u7a76\u6240 \u201d<\/strong><\/span><\/p>\n

\u96c6\u667a\u4ff1\u4e50\u90e8\u7684\u53e3\u53f7\uff1a<\/span><\/strong><\/p>\n

\u8ba9\u82f9\u679c\u7838\u5f97\u66f4\u731b\u70c8\u4e9b\u5427\uff01\uff01\uff01<\/p>\n

\u96c6\u667a\u4ff1\u4e50\u90e8\u7684\u4f7f\u547d\uff08\u5373\u76ee\u6807\uff09\uff1a<\/span><\/strong><\/p>\n

\u8425\u9020\u81ea\u7531\u4ea4\u6d41\u5b66\u672f\u601d\u60f3\u7684\u5c0f\u751f\u5883\uff0c<\/p>\n

 \u5b55\u80b2\u5f00\u521b\u6027\u7684\u79d1\u5b66\u53d1\u73b0<\/p>\n

\u96c6\u667a\u6bcf\u5468\u7cbe\u54c1\u63a8\u8350<\/span><\/strong>
<\/p>\n

\u6df1\u5ea6\u5b66\u4e60\u5f81\u670d\u590d\u6742\u6027 | \u6df1\u5ea6\u201c\u6df1\u5ea6\u5b66\u4e60\u201d\u8bfb\u4e66\u4f1a\u7b2c1\u671f\u7b14\u8bb0\u968f\u60f3<\/a><\/p>\n

\u535a\u7269\u5b66\u89c6\u89d2\u4e0b\u7684\u8fdb\u5316\u3001\u71b5\u4e0e\u81ea\u7136\u79e9\u5e8f<\/a><\/p>\n

\u5982\u4f55\u638c\u63e1\u5b87\u5b99\uff1f| \u51ef\u98ce-\u96c6\u667a\u7814\u8bfb\u8425\u7b14\u8bb0\u4e4b\u4e00<\/a><\/span><\/p>\n

\u57fa\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u667a\u80fd\u63a7\u5236\u6280\u672f\u53ca\u5176\u53d1\u5c55\u8d8b\u52bf\u8bb2\u5ea7\u56de\u987e | \u539f\u521b\u7cbe\u9009<\/a>
<\/p>\n

\"\u96c6\u667a\"<\/p>\n

\u8ba9\u82f9\u679c\u7838\u5f97\u66f4\u731b\u70c8\u4e9b\u5427\uff01<\/span><\/p>\n

\n

\"\u96c6\u667a\"
<\/p>\n<\/section>\n

\u957f\u6309\u8bc6\u522b\u4e8c\u7ef4\u7801\uff0c\u5173\u6ce8\u96c6\u667aClub\uff0c<\/span><\/p>\n

\u8ba9\u6211\u4eec\u79bb\u79d1\u5b66\u63a2\u7d22\u66f4\u8fd1\u4e00\u6b65\u3002<\/span><\/p>\n

\n

\u59cb\u53d1\u4e8e\u5fae\u4fe1\u516c\u4f17\u53f7\uff1a \u96c6\u667a\u4ff1\u4e50\u90e8 <\/p>\n<\/blockquote>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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