{"id":43060,"date":"2023-06-10T16:43:49","date_gmt":"2023-06-10T08:43:49","guid":{"rendered":"https:\/\/swarma.org\/?p=43060"},"modified":"2023-06-10T16:43:49","modified_gmt":"2023-06-10T08:43:49","slug":"%e5%a4%a7%e6%a8%a1%e5%9e%8b%e7%83%ad%e6%bd%ae%e4%b9%8b%e5%90%8e%e7%9a%84%e6%9c%aa%e6%9d%a5%e6%96%b0%e6%96%b9%e5%90%91%ef%bc%9a%e5%9b%be%e7%a5%9e%e7%bb%8f%e7%bd%91%e7%bb%9c%e4%b8%8e%e7%bb%84%e5%90%88","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=43060","title":{"rendered":"\u5927\u6a21\u578b\u70ed\u6f6e\u4e4b\u540e\u7684\u672a\u6765\u65b0\u65b9\u5411\uff1a\u56fe\u795e\u7ecf\u7f51\u7edc\u4e0e\u7ec4\u5408\u4f18\u5316 | \u6587\u732e\u6c47\u603b"},"content":{"rendered":"
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DeepMind\u63d0\u51fa\u7684\u795e\u7ecf\u7b97\u6cd5\u63a8\u7406\u6280\u672f\u80fd\u591f\u5c06\u7ecf\u5178\u7b97\u6cd5\u7528\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u8fdb\u884c\u6a21\u4eff\uff0c\u5e76\u5b9e\u73b0\u4e86\u4f20\u7edf\u7b97\u6cd5\u7684\u6cdb\u5316\u6027\u548c\u795e\u7ecf\u7f51\u7edc\u7684\u6700\u4f18\u89e3\u7684\u5b8c\u7f8e\u7ed3\u5408\u3002\u8be5\u6280\u672f\u91c7\u7528\u7b97\u6cd5\u5bf9\u9f50\u7684\u601d\u60f3\uff0c\u5373\u5c06\u7b97\u6cd5\u5212\u5206\u6210\u591a\u4e2a\u90e8\u5206\uff0c\u6bcf\u4e2a\u90e8\u5206\u7531\u795e\u7ecf\u7b97\u6cd5\u5efa\u6a21\u3002\u5728\u6b64\u57fa\u7840\u4e0a\uff0c\u63d0\u51fa\u4e86\u65b0\u7684GNN\u67b6\u6784\u548c\u8bad\u7ec3\u673a\u5236\uff0c\u53ef\u6709\u6548\u89e3\u51b3\u590d\u6742\u7684\u7ec4\u5408\u4f18\u5316\u95ee\u9898\uff0c\u540c\u65f6\u63d0\u9ad8\u7b97\u6cd5\u7684\u6cdb\u5316\u80fd\u529b\u3002<\/span><\/section>\n

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        \u8fd9\u7bc7\u6587\u7ae0\u5f15\u5165\u4e86\u7b97\u6cd5\u5bf9\u9f50\u7684\u6982\u5ff5\uff0c\u8fd9\u4e00\u6982\u5ff5\u6784\u6210\u4e86\u795e\u7ecf\u7b97\u6cd5\u63a8\u7406\u7684\u6838\u5fc3\u601d\u60f3\u3002<\/span><\/section>\n

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          Deac A I, Veli\u010dkovi\u0107 P, Milinkovic O, et al. Neural algorithmic reasoners are  implicit planners[J]. Advances in Neural Information  Processing  Systems,  2021,  34:  15529-15542.<\/span><\/section>\n<\/li>\n<\/ol>\n
          \u8fd9\u7bc7\u6587\u7ae0\u4ee5\u9690\u5f0f\u7684\u65b9\u5f0f\u4ecb\u7ecd\u4e86\u57fa\u4e8eGNN\u7684\u7b97\u6cd5\u63a8\u7406\u6846\u67b6\uff0c\u5177\u6709\u8f83\u597d\u7684\u6cdb\u5316\u6027\u80fd\u3002<\/span><\/section>\n

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          1. \n
            Ibarz B, Kurin V, Papamakarios G, et al. A generalist neural algorithmic learner[C]. Learning on Graphs Conference. PMLR, 2022: 2: 1-2: 23.<\/span><\/section>\n<\/li>\n<\/ol>\n
            \u8fd9\u7bc7\u6587\u7ae0\u63d0\u51fa\u4e00\u4e2a\u901a\u7528\u7684\u795e\u7ecf\u7b97\u6cd5\u63a8\u7406\u5668\uff0c\u8be5\u6a21\u578b\u4f9d\u8d56\u5355\u4e00\u53c2\u6570\u96c6\u7684GNN\uff0c\u80fd\u591f\u540c\u65f6\u5b66\u4e60\u8bf8\u5982\u6392\u5e8f\u3001\u641c\u7d22\u3001\u8d2a\u5fc3\u7b97\u6cd5\u3001\u52a8\u6001\u89c4\u5212\u3001\u56fe\u7b97\u6cd5\u3001\u5b57\u7b26\u4e32\u6392\u5e8f\u548c\u51e0\u4f55\u7b97\u6cd5\u7b49\u7ecf\u5178\u7b97\u6cd5\u4efb\u52a1\uff0c\u5e76\u4e14\u8fbe\u5230\u4e13\u5bb6\u6a21\u578b\u7684\u5e73\u5747\u6c34\u5e73\u3002<\/span><\/section>\n


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            1. \u81ea\u56de\u5f52\u7b80\u4ecb<\/span><\/strong><\/h5>\n

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            \u81ea\u56de\u5f52\u65b9\u5f0f\u662f\u6307\u5728\u56fe\u795e\u7ecf\u7f51\u7edc\u4e2d\uff0c\u5c06\u89e3\u7684\u751f\u6210\u8fc7\u7a0b\u5efa\u6a21\u4e3a\u4e00\u4e2a\u9010\u6b65\u751f\u6210\u7684\u8fc7\u7a0b\u3002\u6bcf\u4e00\u6b65\u751f\u6210\u4e00 \u4e2a\u89e3\u7684\u4e00\u90e8\u5206\uff0c\u5e76\u4f7f\u7528\u5df2\u751f\u6210\u7684\u90e8\u5206\u6765\u6307\u5bfc\u4e0b\u4e00\u6b65\u7684\u751f\u6210\u3002\u8fd9\u79cd\u65b9\u5f0f\u7684\u4f18\u70b9\u662f\u53ef\u4ee5\u5728\u751f\u6210\u8fc7\u7a0b\u4e2d\u52a8\u6001\u5730\u8003\u8651\u7ea6\u675f\u6761\u4ef6\u548c\u4f18\u5316\u76ee\u6807\uff0c\u4f46\u7f3a\u70b9\u662f\u751f\u6210\u901f\u5ea6\u76f8\u5bf9\u8f83\u6162\u3002<\/span><\/section>\n

            <\/span><\/section>\n
            \u4e3b\u8981\u53c2\u8003\u6587\u732e<\/span><\/section>\n
              \n
            1. \n
              Khalil E, Dai H, Zhang Y, et al. Learning combinatorial optimization algorithms over graphs[J]. Advances in neural information processing systems, 2017, 30.<\/span><\/section>\n<\/li>\n<\/ol>\n
              \u8fd9\u7bc7\u6587\u7ae0\u63a2\u8ba8\u4e86\u7ec4\u5408\u4f18\u5316\u95ee\u9898\u7684\u4e00\u822c\u5f62\u5f0f\uff0c\u63d0\u51fa\u4e86\u4e00\u79cd\u4f7f\u7528\u81ea\u56de\u5f52\u65b9\u5f0f\u5b66\u4e60\u56fe\u4e0a\u7ec4\u5408\u4f18\u5316\u95ee\u9898\u7684\u6c42\u89e3\u7b97\u6cd5\u3002<\/span><\/section>\n

              <\/span><\/section>\n
                \n
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                Fan C, Zeng L, Sun Y, et al. Finding key players in complex networks through deep reinforcement learning[J]. Nature machine intelligence, 2020, 2(6): 317-324.<\/span><\/section>\n<\/li>\n<\/ol>\n
                \u8fd9\u7bc7\u6587\u7ae0\u63d0\u51fa\u57fa\u4e8e\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u6846\u67b6\uff0c\u8be5\u6846\u67b6\u53ef\u4ee5\u5728\u5c0f\u578b\u7f51\u7edc\u4e0a\u8fdb\u884c\u8bad\u7ec3\uff0c\u4ee5\u7406\u89e3\u590d\u6742\u7f51\u7edc\u7cfb\u7edf\u7684\u7ec4\u7ec7\u539f\u5219\uff0c\u4ece\u800c\u5e2e\u52a9\u6211\u4eec\u8bbe\u8ba1\u66f4\u52a0\u6297\u653b\u51fb\u548c\u6297\u6545\u969c\u7684\u7f51\u7edc\u3002<\/span><\/section>\n

                <\/section>\n
                \u89c6\u9891\u8d44\u6599\u63a8\u8350\uff1a\u5229\u7528\u5f3a\u5316\u5b66\u4e60\u5bfb\u627e\u590d\u6742\u7cfb\u7edf\u7684\u5173\u952e\u8282\u70b9\uff0c\u8303\u957f\u4fca<\/span><\/section>\n
                https:\/\/campus.swarma.org\/course\/1808<\/span><\/section>\n

                <\/span><\/section>\n
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                1. \n
                  Bello I, Pham H, Le Q V, et al. Neural combinatorial optimization with reinforcement learning[J]. arXiv preprint arXiv:1611.09940, 2016.<\/span><\/section>\n<\/li>\n<\/ol>\n
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                  <\/span><\/section>\n
                    \n
                  1. \n
                    Amos B, Kolter J Z. Optnet: Differentiable optimization as a layer in neural networks[C]\/\/International Conference on Machine Learning. PMLR, 2017: 136-145.<\/span><\/section>\n<\/li>\n<\/ol>\n
                    \u8fd9\u7bc7\u6587\u7ae0\u63d0\u51fa\u4e00\u79cd\u65b0\u7684\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\uff0c\u5c06\u4f18\u5316\u95ee\u9898\u4f5c\u4e3a\u5355\u72ec\u7684layer\u96c6\u6210\u5230\u66f4\u5927\u7684\u7aef\u5230\u7aef\u53ef\u8bad\u7ec3\u7684\u6df1\u5ea6\u7f51\u7edc\u4e2d\u3002<\/span><\/section>\n

                    <\/span><\/section>\n
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                      Kool W, Van Hoof H, Welling M. Attention, learn to solve routing problems![J]. arXiv preprint arXiv:1803.08475, 2018.<\/span><\/section>\n<\/li>\n<\/ol>\n
                      \u8be5\u8bba\u6587\u63d0\u51fa\u4e86\u4e00\u79cd\u57fa\u4e8e\u6ce8\u610f\u529b\u673a\u5236\u7684\u56fe\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\uff0c\u7528\u4e8e\u89e3\u51b3\u8def\u7531\u95ee\u9898\u3002\u8be5\u65b9\u6cd5\u80fd\u591f\u6709\u6548\u5730\u5b66\u4e60\u8def\u7531\u95ee\u9898\u7684\u7ed3\u6784\u7279\u5f81\uff0c\u5e76\u5728\u6d4b\u8bd5\u96c6\u4e0a\u53d6\u5f97\u4e86\u4f18\u5f02\u7684\u6027\u80fd\u3002<\/span><\/section>\n

                      <\/span><\/section>\n
                      \u89c6\u9891\u8d44\u6599\u63a8\u8350\uff1a\u6ce8\u610f\u529b\u6a21\u578b\u5b66\u4e60\u6c42\u89e3\u8def\u5f84\u95ee\u9898\uff0c\u725f\u7267\u4e91<\/span><\/section>\n
                      https:\/\/campus.swarma.org\/course\/1052<\/span><\/section>\n

                      <\/h5>\n
                      2. \u975e\u81ea\u56de\u5f52\u7b80\u4ecb<\/span><\/strong><\/h5>\n

                      <\/section>\n
                      \u975e\u81ea\u56de\u5f52\u65b9\u5f0f\u662f\u6307\u5728\u56fe\u795e\u7ecf\u7f51\u7edc\u4e2d\uff0c\u5c06\u6574\u4e2a\u95ee\u9898\u7684\u6c42\u89e3\u8fc7\u7a0b\u4f5c\u4e3a\u4e00\u4e2a\u6574\u4f53\u8fdb\u884c\u6c42\u89e3\uff0c\u4e00\u6b21\u6027 \u8f93\u51fa\u6700\u7ec8\u7684\u89e3\u3002\u8fd9\u79cd\u65b9\u5f0f\u7684\u4f18\u70b9\u662f\u6c42\u89e3\u901f\u5ea6\u8f83\u5feb\uff0c\u4f46\u7f3a\u70b9\u662f\u4e0d\u80fd\u52a8\u6001\u5730\u8003\u8651\u7ea6\u675f\u6761\u4ef6\u548c\u4f18\u5316\u76ee\u6807\u3002<\/span><\/section>\n

                      <\/span><\/section>\n
                      \u4e3b\u8981\u53c2\u8003\u6587\u732e<\/span><\/section>\n

                      <\/span><\/section>\n
                        \n
                      1. \n
                        Li Z, Chen Q, Koltun V. Combinatorial optimization with graph convolutional networks and guided tree search[J]. Advances in neural information processing systems, 2018, 31.<\/span><\/section>\n<\/li>\n<\/ol>\n
                        \u8fd9\u7bc7\u8bba\u6587\u4e3b\u8981\u4ecb\u7ecd\u4e86\u4e00\u79cd\u7ed3\u5408\u56fe\u5377\u79ef\u7f51\u7edc\uff08GCN\uff09\u548c\u5f15\u5bfc\u6811\u641c\u7d22\uff08Guided Tree Search\uff09\u7684\u7ec4\u5408\u4f18\u5316\u7b97\u6cd5\uff0c\u7528\u4e8e\u89e3\u51b3\u5305\u62ec\u65c5\u884c\u5546\u95ee\u9898\uff08TSP\uff09\u548c\u8f66\u8f86\u8def\u5f84\u95ee\u9898\uff08VRP\uff09\u7b49\u4e00\u7cfb\u5217NP\u96be\u95ee\u9898\u3002\u8be5\u7b97\u6cd5\u4f7f     \u7528GCN\u6a21\u578b\u6765\u4ece\u56fe\u5f62\u8f93\u5165\u4e2d\u63d0\u53d6\u7279\u5f81\uff0c\u5e76\u5c06\u5176\u8f93\u5165\u5230\u5f15\u5bfc\u6811\u641c\u7d22\u4e2d\uff0c\u5f15\u5bfc\u6811\u641c\u7d22\u4f7f\u7528GCN\u6a21\u578b\u63d0\u4f9b   \u7684\u542f\u53d1\u5f0f\u4fe1\u606f\u6765\u6307\u5bfc\u641c\u7d22\u8fc7\u7a0b\u3002<\/span><\/section>\n

                        <\/span><\/section>\n
                        \u89c6\u9891\u8d44\u6599\u63a8\u8350\uff1a\u7ed3\u5408\u56fe\u5377\u79ef\u7f51\u7edc\u7684\u7ec4\u5408\u4f18\u5316\u548c\u6811\u641c\u7d22\uff0c\u5218\u6676<\/span><\/section>\n
                        https:\/\/campus.swarma.org\/course\/1086<\/span><\/section>\n

                        <\/span><\/section>\n
                          \n
                        1. \n
                          Fu Z H, Qiu K B, Zha H. Generalize a small pre-trained model to arbitrarily large tsp instances[C]\/\/Proceedings of the AAAI Conference on Artificial Intelligence. 2021, 35(8): 7474- 7482.<\/span><\/section>\n<\/li>\n<\/ol>\n
                          \u8fd9\u7bc7\u6587\u7ae0\u5c1d\u8bd5\u91c7\u7528\u76d1\u7763\u5b66\u4e60\u65b9\u5f0f\uff0c\u8bad\u7ec3\u4e00\u4e2a\u5c0f\u89c4\u6a21\u7684\u6a21\u578b\uff0c\u5229\u7528\u56fe\u91c7\u6837\u3001\u56fe\u8f6c\u6362\u4ee5\u53ca\u70ed\u56fe\u5408\u5e76\u7b49\u4e00 \u7cfb\u5217\u6280\u672f\uff0c\u6784\u5efa\u53ef\u91cd\u590d\u7528\u4e8e\u4efb\u610f\u89c4\u6a21TSP\u5b9e\u4f8b\u7684\u70ed\u56fe\u3002\u6b64\u5916\uff0c\u901a\u8fc7\u8f93\u5165\u70ed\u56fe\u5230\u5f3a\u5316\u5b66\u4e60\u65b9\u6cd5(\u8499\u7279\u5361 \u6d1b\u6811\u641c\u7d22)\uff0c\u4ee5\u6307\u5bfc\u641c\u7d22\u9ad8\u8d28\u91cf\u7684\u89e3\u51b3\u65b9\u6848\u3002<\/span><\/section>\n

                          <\/span><\/section>\n
                            \n
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                            Nazari M, Oroojlooy A, Snyder L, et al. Reinforcement learning for solving the vehicle routing problem[J]. Advances in neural information processing systems, 2018, 31.<\/span><\/section>\n<\/li>\n<\/ol>\n
                            \u8fd9\u7bc7\u6587\u7ae0\u91c7\u7528\u56fe\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u548c\u5f3a\u5316\u5b66\u4e60\u6765\u89e3\u51b3\u8f66\u8f86\u8def\u5f84\u95ee\u9898\u3002<\/span><\/section>\n

                            <\/span><\/section>\n
                              \n
                            1. \n
                              Chalumeau F, Coulon I, Cappart Q, et al. Seapearl: A constraint programming solver guided by reinforcement learning[C]\/\/Integration of Constraint Programming, Artificial Intelligence, and Operations Research: 18th International Conference, CPAIOR 2021, Vienna, Austria, July 5\u20138, 2021, Proceedings 18. Springer International Publishing, 2021: 392-409.<\/span><\/section>\n<\/li>\n<\/ol>\n
                              \u8fd9\u7bc7\u6587\u7ae0\u5c06\u7ea6\u675f\u6ee1\u8db3\u95ee\u9898\uff08CSP\uff09\u5efa\u6a21\u6210\u7b80\u5355\u7684\u3001\u65e0\u5411\u7684\u4e09\u90e8\u56fe\u3002\u5728\u8be5\u56fe\u4e0a\uff0c\u6bcf\u4e2a\u53d8\u91cf\u3001\u53ef\u80fd\u7684\u53d6   \u503c\u548c\u7ea6\u675f\u90fd\u7528\u8282\u70b9\u8868\u793a\u3002\u5f53\u4e14\u4ec5\u5f53\u4e00\u4e2a\u53d8\u91cf\u6d89\u53ca\u5230\u4e00\u4e2a\u7ea6\u675f\uff0c\u6216\u8005\u5f53\u4e00\u4e2a\u503c\u5728\u4e00\u4e2a\u53d8\u91cf\u7684\u53ef\u9009\u53d6\u503c \u96c6\u5408\u4e2d\u65f6\uff0c\u76f8\u5e94\u7684\u8282\u70b9\u624d\u7531\u4e00\u6761\u8fb9\u8fde\u63a5\u3002<\/span><\/section>\n

                              <\/span><\/section>\n
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                                Pogan\u010di\u0107 M V, Paulus A, Musil V, et al. Differentiation of blackbox combinatorial solvers[C]\/\/International Conference on Learning Representations. 2020.<\/span><\/section>\n<\/li>\n<\/ol>\n
                                \u56fe\u795e\u7ecf\u7f51\u7edc\u5728\u5904\u7406\u81ea\u7136\u8f93\u5165\u7b49\u4e0a\u6e38\u4efb\u52a1\u4e2d\u53d1\u6325\u7740\u91cd\u8981\u4f5c\u7528\uff0c\u53ef\u76f4\u63a5\u4ece\u81ea\u7136\u8f93\u5165\u5982\u56fe\u7247\u3001\u8bed\u97f3\u548c\u6587\u672c\u7b49\u4e2d\u63d0\u53d6\u7279\u5f81\uff0c\u5e76\u5e94\u7528\u4e8e\u7ec4\u5408\u4f18\u5316\u95ee\u9898\u7684\u6c42\u89e3\u3002\u8fd9\u7bc7\u8bba\u6587\u6a21\u578b\u7684\u81ea\u7136\u8f93\u5165\u4e3a\u56fe\u7247\uff0c\u5229\u7528\u795e\u7ecf\u7f51\u7edc\u89e3\u51b3TSP\u3001\u6700\u77ed\u8def\u5f84\u7b49\u7ec4\u5408\u4f18\u5316\u95ee\u9898\u3002<\/span><\/section>\n

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

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

                                \u4e3b\u9898\u4e09\uff1a\u56fe\u795e\u7ecf\u7f51\u7edc\u4e0e\u7ec4\u5408\u4f18\u5316\u2014\u2014\u5c40\u90e8\u6539\u8fdb\u6c42\u89e3<\/span><\/strong><\/span><\/h4>\n

                                <\/section>\n
                                \u7b80\u4ecb<\/span><\/section>\n
                                \u56fe\u795e\u7ecf\u7f51\u7edc\u91c7\u7528\u5c40\u90e8\u6539\u8fdb\u6c42\u89e3\u7ec4\u5408\u4f18\u5316\u95ee\u9898\u4e3b\u8981\u5305\u62ec\u4e24\u79cd\u65b9\u5f0f\uff0c\u4e00\u79cd\u662f\u6539\u8fdb\u7cbe\u786e\u7b97\u6cd5\uff0c\u5982\u5206\u652f\u5b9a \u754c\u6cd5\u4e2d\u7684\u5206\u652f\u7528\u5206\u7c7b\u5b66\u4e60\u4ee3\u66ff\uff1b\u53e6\u4e00\u79cd\u5219\u662f\u5c40\u90e8\u6539\u8fdb\u542f\u53d1\u5f0f\u7b97\u6cd5\uff0c\u5982\u6539\u8fdb\u6a21\u62df\u9000\u706b\u4e2d\u7684\u9000\u706b\u673a\u5236\u3002<\/span><\/section>\n

                                <\/span><\/section>\n
                                1. \u5c40\u90e8\u6539\u8fdb\u7cbe\u786e\u7b97\u6cd5<\/span><\/strong><\/h5>\n

                                <\/section>\n
                                \u4e3b\u8981\u53c2\u8003\u6587\u732e<\/span><\/section>\n
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                                  Gasse M, Ch\u00e9telat D, Ferroni N, et al. Exact combinatorial optimization with graph convolutional neural networks[J]. Advances in neural information processing systems, 2019, 32.<\/span><\/section>\n<\/li>\n<\/ol>\n
                                  \u8fd9\u7bc7\u6587\u7ae0\u5c06MILP\u95ee\u9898\u7684\u53d8\u91cf\u548c\u7ea6\u675f\u5efa\u6a21\u6210\u4e8c\u90e8\u56fe\uff0c\u57fa\u4e8e\u5efa\u6a21\u7684\u4e8c\u90e8\u56fe\uff0c\u91c7\u7528GCN\u548c\u6a21\u4eff\u5b66\u4e60   \u6539\u8fdb\u5206\u652f\u7b56\u7565\u3002<\/span><\/section>\n

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                                    Khalil E, Le Bodic P, Song L, et al. Learning to branch in mixed integer programming[C]. Proceedings of the AAAI Conference on Artificial Intelligence. 2016, 30(1).<\/span><\/section>\n
                                    \u8fd9\u7bc7\u8bba\u6587\u5c06\u56fe\u795e\u7ecf\u7f51\u7edc\u5e94\u7528\u4e8e\u51b3\u7b56\u6811\u7684\u5206\u652f\u9009\u62e9\uff0c\u4ece\u800c\u6539\u8fdb\u4e86\u4f20\u7edf\u7684\u5206\u652f\u7b56\u7565\uff0c\u4ece\u800c\u89e3\u51b3\u6df7\u5408 \u6574\u6570\u89c4\u5212\uff08MIP\uff09\u95ee\u9898\u3002<\/span><\/section>\n

                                    <\/section>\n<\/li>\n
                                  2. \n
                                    Chen X Y, Tian Y D. Learning to perform local rewriting for combinatorial optimization. In: Proceedings of the 33rd Conference on Neural Information Processing Systems. Vancouver, Canada: Curran Associates, Inc., 2019. 6278\u22126289<\/span><\/section>\n<\/li>\n<\/ol>\n
                                    \u8fd9\u7bc7\u6587\u7ae0\u63d0\u51fa\u4e86\u4e00\u4e2a\u57fa\u4e8e\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u7684\u7ec4\u5408\u4f18\u5316\u95ee\u9898\u641c\u7d22\u6a21\u578b NeuRewriter, \u5b83\u548c\u5c40\u90e8\u641c\u7d22\u5177\u6709\u76f8\u4f3c\u7684\u7b97\u6cd5\u6d41\u7a0b,  \u5373\u9996\u5148\u968f\u673a\u6784\u9020\u4e00\u4e2a\u53ef\u884c\u89e3,  \u5728\u8be5\u521d\u59cb\u89e3\u7684\u57fa\u7840\u4e0a\u901a\u8fc7\u5c40\u90e8\u641c\u7d22\u4e0d\u65ad\u63d0\u9ad8\u89e3\u7684\u8d28\u91cf\u3002<\/span><\/section>\n

                                    <\/span><\/section>\n
                                    2. \u5c40\u90e8\u6539\u8fdb\u542f\u53d1\u5f0f\u7b97\u6cd5<\/span><\/strong><\/h5>\n

                                    <\/section>\n
                                    \u4e3b\u8981\u53c2\u8003\u6587\u732e<\/span><\/section>\n

                                    <\/span><\/section>\n
                                      \n
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                                      Mills K, Ronagh P, Tamblyn I. Finding the ground state of spin Hamiltonians with reinforcement learning[J]. Nature Machine Intelligence, 2020, 2(9): 509-517.<\/span><\/section>\n<\/li>\n<\/ol>\n
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                                          \u8fd9\u7bc7\u6587\u7ae0\u91c7\u7528GCN\u5bf9\u8282\u70b9\u7279\u5f81\u8fdb\u884c\u7f16\u7801\uff0c\u7ed3\u5408LKH\u542f\u53d1\u5f0f\u7b97\u6cd5\uff0c\u80fd\u591f\u5728\u4fdd\u8bc1\u7b97\u6cd5\u6548\u7387\u7684\u540c\u65f6\uff0c   \u8fdb\u4e00\u6b65\u63d0\u9ad8\u6c42\u89e3\u7cbe\u5ea6\u3002<\/span><\/section>\n


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                                          \u7b80\u4ecb\uff1a\u65e0\u8bba\u662f\u5fae\u89c2\u4e16\u754c\u4e2d\u7684\u5206\u5b50\u3001\u86cb\u767d\u8d28\u3001\u6297\u4f53\u3001RNA\uff0c\u8fd8\u662f\u5b8f\u89c2\u4e16\u754c\u4e2d\u7684\u673a\u68b0\u7cfb\u7edf\u3001\u4e0d\u540c\u5f62\u72b6\u7684\u7269\u4f53\u7b49\uff0c\u6784\u6210\u4e86\u4e00\u7c7b\u91cd\u8981\u7684\u6570\u636e\u5f62\u6001\u2014\u2014\u51e0\u4f55\u56fe\u3002\u4e0e\u793e\u4ea4\u7f51\u7edc\u4e2d\u7684\u62d3\u6251\u56fe\u4e0d\u540c\uff0c\u51e0\u4f55\u56fe\u4e2d\u7684\u8282\u70b9\u5360\u636e\u4e86\u4e00\u5b9a\u7684\u7a7a\u95f4\u4f4d\u7f6e\uff0c\u9700\u8981\u6ee1\u8db3\u67d0\u4e9b\u5185\u8574\u7684\u7269\u7406\u6027\u8d28\uff0c\u6bd4\u5982\u5bf9\u79f0\u6027\uff0c\u5bfc\u81f4\u4f20\u7edf\u7684\u56fe\u795e\u7ecf\u7f51\u7edc\u96be\u4ee5\u5904\u7406\u51e0\u4f55\u56fe\u3002<\/span><\/section>\n

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                                          \u8fd1\u5e74\u6765\uff0c\u4e0d\u53d8\u548c\u7b49\u53d8\u56fe\u795e\u7ecf\u7f51\u7edc\u8003\u8651\u4e86\u5bf9\u79f0\u6027\uff0c\u5177\u6709\u826f\u597d\u7684\u89e3\u91ca\u6027\u3001\u6cdb\u5316\u6027\u548c\u901a\u7528\u6027\uff0c\u80fd\u6709\u6548\u5b9e\u73b0\u51e0\u4f55\u56fe\u7684\u5904\u7406\u548c\u5206\u6790\u3002\u51e0\u4f55\u56fe\u795e\u7ecf\u7f51\u7edc\u5728\u7269\u7406\u7cfb\u7edf\u6a21\u62df\u3001\u86cb\u767d\u8d28\u6298\u53e0\u9884\u6d4b\uff08\u5982\u4e3b\u9898\u4e94\u4e2d\u7684RoseTTAFold\u8bba\u6587\uff09\u3001\u6297\u4f53\u8bbe\u8ba1\uff08\u5982\u4e3b\u9898\u4e94\u4e2d\u7684MEAN\u8bba\u6587\uff09\u7b49\u95ee\u9898\u4e0a\u5f97\u5230\u4e86\u6210\u529f\u5e94\u7528\u3002<\/span><\/section>\n

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                                          1. \u4e0d\u53d8\u56fe\u795e\u7ecf\u7f51\u7edc<\/span><\/strong><\/h5>\n

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                                                <\/h5>\n
                                                2. \u7b49\u53d8\u56fe\u795e\u7ecf\u7f51\u7edc<\/span><\/strong><\/h5>\n

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                                                \u5bf9\u6a21\u578b\u8f93\u5165\u505a\u4e00\u5b9a\u7684\u53d8\u6362\u4e4b\u540e\uff0c\u6a21\u578b\u8f93\u51fa\u505a\u540c\u6837\u7684\u53d8\u6362\u3002<\/span><\/section>\n

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                                                      \u4e2d\u56fd\u79d1\u5b66\u9662\u9662\u58eb\u9102\u7ef4\u5357\u6559\u6388\u63d0\u51fa\u57fa\u7840\u5b66\u79d1\u53d1\u5c55\u65b0\u7684\u66d9\u5149\uff1aAI for Science\u5c06\u4eba\u5de5\u667a\u80fd\u4e0e\u57fa\u7840\u79d1\u5b66\u6df1\u5ea6\u878d\u5408\u3002\u79d1\u5b66\u9886\u57df\u7684\u8bb8\u591a\u95ee\u9898\u672c\u8d28\u4e0a\u662f\u5bf9\u7269\u7406\u7cfb\u7edf\u7684\u5904\u7406\u548c\u5206\u6790\uff0c\u800c\u7269\u7406\u7cfb\u7edf\u662f\u53ef\u4ee5\u5efa\u6a21\u6210\u56fe\u8c31\u3002\u56e0\u6b64\uff0c\u56fe\u795e\u7ecf\u7f51\u7edc\u662fAI for Science\u9886\u57df\u7684\u57fa\u7840\u5de5\u5177\uff0c\u6781\u5927\u63a8\u52a8\u4e86AI\u5728\u5206\u5b50\u52a8\u529b\u5b66\u6a21\u62df\u3001\u6750\u6599\u8bbe\u8ba1\u3001\u836f\u7269\u53d1\u73b0\u7b49\u4efb\u52a1\u4e0a\u7684\u5e94\u7528\u524d\u666f\u3002<\/span><\/section>\n

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                                                              Xiangzhe Kong, Wenbing Huang, Yang Liu. Conditional Antibody Design as 3D Equivariant Graph Translation. ICLR, 2023.<\/span><\/section>\n
                                                              \u7b80\u79f0MEAN\uff0c\u4f7f\u7528\u4e86\u7b49\u53d8\u56fe\u795e\u7ecf\u7f51\u7edc\u5b8c\u6210\u6297\u4f53CDR\u533a\u57df1D\u6c28\u57fa\u9178\u5e8f\u5217\u548c3D\u7ed3\u6784\u7684\u540c\u65f6\u751f\u6210\u548c\u4f18\u5316\u3002<\/span><\/section>\n


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                                                              \u6b22<\/span>\u8fce<\/span>\u626b\u7801\u67e5\u770b<\/span>\u672c\u6b21\u8bfb\u4e66\u4f1a\u7684\u5b8c\u6574\u8bba\u6587\u5217\u8868\u4e0e\u76f8\u5173\u5b66\u4e60\u8d44\u6e90\uff1a<\/span>
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                                                              \u8def\u5f84\u5730\u5740\uff1ahttps:\/\/pattern.swarma.org\/article\/226<\/span><\/section>\n

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                                                              \u56fe\u7f51\u7edc\u5165\u95e8\u8def\u5f84\uff1a\u4ece\u7f51\u7edc\u79d1\u5b66\u89c6\u89d2\u51fa\u53d1\uff0c\u4e0a\u624b\u6df1\u5ea6\u5b66\u4e60\u524d\u6cbf\u6280\u672f<\/span><\/a><\/p>\n

                                                              \u56fe\u7f51\u7edc\u2014\u2014\u6084\u7136\u5174\u8d77\u7684\u6df1\u5ea6\u5b66\u4e60\u65b0\u6d6a\u6f6e | AI&Society\u7b2c\u516b\u671f\u56de\u987e\uff08\u603b\u7ed3\u6587\u7ae0\uff09<\/span><\/a><\/p>\n

                                                              \u9762\u5411\u7ec4\u5408\u4f18\u5316\u95ee\u9898\u7684\u56fe\u5b66\u4e60\u7efc\u8ff0<\/span><\/a><\/p>\n

                                                              \u6df1\u5ea6\u5b66\u4e60\u4e2d\u7684\u62d3\u6251\u7f8e\u5b66\uff1aGNN\u57fa\u7840\u4e0e\u5e94\u7528<\/span><\/a><\/section>\n
                                                              Nat. Mach. Intell. \u901f\u9012\uff1a\u56fe\u795e\u7ecf\u7f51\u7edc\u5b9e\u73b0\u4e09\u7ef4\u6d41\u4f53\u8fd0\u52a8\u4e2d\u7684\u7c92\u5b50\u8ddf\u8e2a<\/span><\/a><\/section>\n
                                                              Barab\u00e1si \u6700\u65b0\u7814\u7a76\uff1a\u5229\u7528\u56fe\u795e\u7ecf\u7f51\u7edc\u52a0\u901f\u7f51\u7edc\u5e03\u5c40<\/span><\/a>
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                                                              Nat. Commun. \u901f\u9012\uff1a\u56fe\u795e\u7ecf\u7f51\u7edc\u9884\u6d4b\u5355\u4e2a\u86cb\u767d\u8d28\u7ed3\u6784\u4e2d\u9690\u85cf\u53e3\u888b\u7684\u4f4d\u7f6e<\/span><\/a>
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