{"id":48652,"date":"2024-02-29T21:49:09","date_gmt":"2024-02-29T13:49:09","guid":{"rendered":"https:\/\/swarma.org\/?p=48652"},"modified":"2024-02-29T21:49:09","modified_gmt":"2024-02-29T13:49:09","slug":"%e5%a4%a7%e8%af%ad%e8%a8%80%e6%a8%a1%e5%9e%8b%e4%b8%8e%e5%a4%9a%e6%99%ba%e8%83%bd%e4%bd%93%e7%b3%bb%e7%bb%9f%e8%af%bb%e4%b9%a6%e4%bc%9a%e6%9c%ac%e5%91%a8%e5%85%ad%e5%bc%80%e5%a7%8b","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=48652","title":{"rendered":"\u201c\u5927\u8bed\u8a00\u6a21\u578b\u4e0e\u591a\u667a\u80fd\u4f53\u7cfb\u7edf\u8bfb\u4e66\u4f1a\u201d\u672c\u5468\u516d\u5f00\u59cb\u5566\uff01"},"content":{"rendered":"
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                \u7814\u7a76\u65b9\u5411\uff1a\u4f7f\u7528LLM\u548cLLM-based Agents\u89e3\u51b3\u79d1\u5b66\u9886\u57df\u63a8\u7406\u548c\u89c4\u5212\u95ee\u9898, AI4Science\u4ee5\u53ca\u63a8\u8350\u7cfb\u7edf\uff0c\u4ee5\u4e00\u4f5c\u5728NeurIPS\u3001WWW\u7b49\u4f1a\u8bae\u4e0a\u53d1\u8868\u6587\u7ae0\uff0c\u540c\u65f6\u83b7\u5f97\u8fc7KDD Cup, NeurIPS BlackBox Optimization Challenge, IEEE Computer Society Challenge\u7b49\u673a\u5668\u5b66\u4e60\u7ade\u8d5b\u7684\u51a0\/\u4e9a\u519b\u3002<\/span><\/section>\n


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                \u7814\u7a76\u65b9\u5411\uff1a\u5305\u62ec\u81ea\u4e3b\u4ee3\u7406\u3001\u56fe\u5f62\u673a\u5668\u5b66\u4e60\u3001\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u5d4c\u5165\u5f0f\u4eba\u5de5\u667a\u80fd\u3002\u4ed6\u5728ICCV\u3001CVPR\u3001ICML\u3001NeurIPS\u3001RSS\u30013DV\u548cTPAMI\u7b49\u9876\u7ea7\u4f1a\u8bae\u548c\u671f\u520a\u4e0a\u53d1\u8868\u4e86\u76f8\u5173\u8bba\u6587\u3002<\/span><\/section>\n

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                \u4efb\u6c81\u6e90<\/span><\/strong>\uff0c<\/span>2008\u5e74\u5728\u6d59\u6c5f\u5927\u5b66\u63a7\u5236\u79d1\u5b66\u4e0e\u5de5\u7a0b\u4e13\u4e1a\u83b7\u5f97\u535a\u58eb\u5b66\u4f4d\u3002\u968f\u540e\u52a0\u5165\u65b0\u52a0\u5761\u56fd\u7acb\u5927\u5b66\u8ba1\u7b97\u673a\u4e0e\u7535\u6c14\u5de5\u7a0b\u5b66\u7cfb\u4ece\u4e8b\u6c34\u4e0b\u65e0\u4eba\u667a\u80fd\u7cfb\u7edf\u7684\u63a7\u5236\u7814\u7a76\u3002\u4ece2015\u5e747\u6708\u5f00\u59cb\uff0c\u52a0\u5165\u65b0\u52a0\u5761\u79d1\u6280\u7814\u7a76\u5c40\u8d44\u8baf\u7814\u7a76\u9662\u62c5\u4efb\u673a\u5668\u4eba\u7814\u7a76\u79d1\u5b66\u5bb6\u30022017\u5e74\u8d77\u52a0\u5165\u6d59\u6c5f\u5927\u5b66\u62c5\u4efb\u6559\u6388\u3002\u4efb\u6c81\u6e90\u535a\u58eb\u76ee\u524d\u662fIEEE Senior Member\uff0c\u5e76\u62c5\u4efb\u591a\u672c\u56fd\u9645\u5b66\u672f\u671f\u520a\u7684\u7f16\u8f91\u3002\u4ed6\u4e3b\u8981\u4ece\u4e8b\u8fd0\u52a8\u63a7\u5236\uff0c\u4eff\u751f\u667a\u80fd\u548c\u4eba\u673a\u4ea4\u4e92\u7b49\u7814\u7a76\u5de5\u4f5c\u3002<\/span><\/span><\/p>\n

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                [1] Guo T, Chen X, Wang Y, et al. Large language model based multi-agents: A survey of progress and challenges[J]. arXiv preprint arXiv:2402.01680, 2024.<\/span><\/p>\n

                [2] Sumers T R, Yao S, Narasimhan K, et al. Cognitive architectures for language agents[J]. arXiv preprint arXiv:2309.02427, 2023.<\/span><\/p>\n

                [3] Hong S, Zheng X, Chen J, et al. Metagpt: Meta programming for multi-agent collaborative framework[J]. arXiv preprint arXiv:2308.00352, 2023.<\/span><\/p>\n

                [4] Li G, Hammoud H A A K, Itani H, et al. Camel: Communicative agents for” mind” exploration of large scale language model society[J]. arXiv preprint arXiv:2303.17760, 2023.<\/span><\/section>\n

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                \u76f4\u64ad\u4fe1\u606f<\/strong><\/span><\/strong><\/strong><\/p>\n<\/section>\n

                \n

                <\/section>\n

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


                <\/p>\n

                \u65f6\u95f4\uff1a<\/span><\/strong><\/span><\/section>\n
                2024\u5e743\u67082\u65e5\uff08\u672c\u5468\u516d\uff09\u665a\u4e0a20:00-22:00\u3002<\/span><\/section>\n

                <\/span><\/section>\n
                \u53c2\u4e0e\u65b9\u5f0f\uff1a<\/span><\/strong><\/span><\/section>\n
                <\/mp-common-videosnap><\/section>\n
                <\/span><\/strong><\/section>\n
                <\/section>\n
                \u626b\u7801\u53c2\u4e0e\u591a\u667a\u80fd\u4f53\u8bfb\u4e66\u4f1a<\/a>\uff0c\u52a0\u5165\u7fa4\u804a\uff0c\u83b7\u53d6\u7cfb\u5217\u8bfb\u4e66\u4f1a\u56de\u770b\u6743\u9650\uff0c\u4e0e\u793e\u533a\u7684\u4e00\u7ebf\u79d1\u7814\u5de5\u4f5c\u8005\u4e0e\u4f01\u4e1a\u5b9e\u8df5\u8005\u6c9f\u901a\u4ea4\u6d41\uff0c\u5171\u540c\u63a8\u52a8\u591a\u667a\u80fd\u4f53\u8fd9\u4e00\u524d\u6cbf\u9886\u57df\u7684\u53d1\u5c55\u3002<\/span><\/section>\n

                <\/section>\n

                <\/section>\n

                \n
                \n
                \n
                \n
                \n

                <\/section>\n

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

                \u7279\u522b\u81f4\u8c22\u5355\u4f4d<\/strong><\/span><\/strong><\/strong><\/p>\n<\/section>\n

                \n

                <\/section>\n

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


                <\/p>\n

                Datawhale<\/span><\/strong><\/span><\/h4>\n
                \u4e00\u4e2a\u4e13\u6ce8\u4e8eAI\u9886\u57df\u7684\u5f00\u6e90\u7ec4\u7ec7\uff0c\u6c47\u805a\u4e86\u4f17\u591a\u4f18\u79c0\u5b66\u4e60\u8005\uff0c\u4f7f\u547dfor the learner\uff0c\u548c\u5b66\u4e60\u8005\u4e00\u8d77\u6210\u957f\u3002<\/span><\/section>\n


                <\/h4>\n

                Agent42<\/span><\/strong><\/span><\/h4>\n
                \u4e00\u4e2a\u81f4\u529b\u4e8e\u63a8\u8fdbAI Agents\u4ea7\u5b66\u7814\u878d\u5408\u53ca\u521b\u65b0\u7684\u751f\u6001\u5f00\u653e\u5e73\u53f0<\/span><\/section>\n


                <\/p>\n

                \u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u62a5\u540d\u8bfb\u4e66\u4f1a<\/span><\/section>\n

                <\/mp-style-type><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

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