{"id":22222,"date":"2020-11-29T19:24:32","date_gmt":"2020-11-29T11:24:32","guid":{"rendered":"https:\/\/swarma.org\/?p=22222"},"modified":"2020-11-29T19:24:32","modified_gmt":"2020-11-29T11:24:32","slug":"%e4%bb%8a%e6%99%9a8%e7%82%b9%e7%9b%b4%e6%92%ad%ef%bc%9a%e5%9b%a0%e6%9e%9c%e5%bc%ba%e5%8c%96%e5%ad%a6%e4%b9%a0-%e5%9b%a0%e6%9e%9c%e7%a7%91%e5%ad%a6%e4%b8%8ecausal-ai%e8%af%bb%e4%b9%a6%e4%bc%9a","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=22222","title":{"rendered":"\u4eca\u665a8\u70b9\u76f4\u64ad\uff1a\u56e0\u679c\u5f3a\u5316\u5b66\u4e60 | \u56e0\u679c\u79d1\u5b66\u4e0eCausal AI\u8bfb\u4e66\u4f1a"},"content":{"rendered":"
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\u4eca\u665a8\u70b9\uff0c\u201c\u56e0\u679c\u79d1\u5b66\u4e0eCausal A<\/span>I\u201d\u8bfb\u4e66\u4f1a\u5c06\u8fdb\u884c\u7b2c\u5341\u671f\u7684\u7ebf\u4e0a\u8bba\u6587\u5206\u4eab\uff0c\u4e3b\u9898\u662f\u201c\u56e0\u679c\u5f3a\u5316\u5b66\u4e60<\/span><\/span>\u201d\uff0c\u5c06\u7531\u5251\u6865\u5927\u5b66\u5728\u8bfb\u535a\u58eb<\/span>\u9646\u8d85\u8d85\u3001\u6e05\u534e\u5927\u5b66\u5728\u8bfb\u535a\u58eb<\/span>\u5f20\u5353\u5a67<\/span><\/span><\/span>\u6765\u8fdb\u884c\u5206\u4eab\uff0c\u672c\u6b21\u5185\u5bb9\u5c06\u5728\u96c6\u667a\u4ff1\u4e50\u90e8B\u7ad9\u76f4\u64ad\u3002<\/span><\/section>\n

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\u4e3b\u9898\u80cc\u666f\u7b80\u4ecb<\/span><\/strong><\/span><\/section>\n

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\u8fd1\u4e9b\u5e74\u6765\uff0c\u5728\u6e38\u620f\u9886\u57df\u5f3a\u5316\u5b66\u4e60\u53d6\u5f97\u4e86\u5de8\u5927\u7684\u8fdb\u5c55\uff0c\u5df2\u7ecf\u80fd\u591f\u6253\u8d25\u4eba\u7c7b\u6700\u9876\u7ea7\u7684\u73a9\u5bb6\u3002\u4f46\u5728\u73b0\u5b9e\u751f\u6d3b\u4e2d\uff0c\u6211\u4eec\u5374\u7f55\u89c1\u5f3a\u5316\u5b66\u4e60\u7684\u6210\u529f\u5e94\u7528\u3002\u5e26\u7740\u8fd9\u79cd\u7591\u60d1\uff0c\u5728\u672c\u6b21\u8bfb\u4e66\u4f1a\u4e0a\uff0c\u6211\u4eec\u5c06\u63a2\u8bbf\u673a\u5668\u5b66\u4e60\u4e2d\u4e00\u4e2a\u5168\u65b0\u7684\u9886\u57df\u2014\u2014\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u3002\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u4e0d\u4ec5\u53ef\u4ee5\u4e3a\u4f20\u7edf\u5f3a\u5316\u5b66\u4e60\u4e2d\u90a3\u4e9b\u68d8\u624b\u7684\u95ee\u9898\u63d0\u4f9b\u4e00\u79cd\u65b0\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u66f4\u91cd\u8981\u7684\u662f\uff0c\u5b83\u8fd8\u4e3a\u901a\u7528\u4eba\u5de5\u667a\u80fd\u63d0\u4f9b\u4e00\u79cd\u89e3\u51b3\u601d\u8def\u3002\u9690\u85cf\u5728\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u80cc\u540e\u7684\u54f2\u5b66\u7406\u5ff5\u662f\u8ff7\u4eba\u7684\uff1a\u56de\u987e\u79d1\u5b66\u53d1\u5c55\u7684\u5386\u53f2\uff0c\u4eba\u7c7b\u4e5f\u662f\u8d70\u7740\u76f8\u4f3c\u7684\u9053\u8def\u3002\u5177\u4f53\u6765\u8bf4\uff0c\u4eba\u7c7b\u662f\u5728\u4e0d\u65ad\u5730\u4e0e\u81ea\u7136\u4ea4\u4e92\u63a2\u7d22\u7684\u8fc7\u7a0b\u4e2d\u603b\u7ed3\u7ecf\u9a8c\u548c\u89c4\u5f8b\uff0c\u7136\u540e\u5229\u7528\u8fd9\u4e9b\u7ecf\u9a8c\u548c\u89c4\u5f8b\u66f4\u597d\u5730\u6307\u5bfc\u4e0b\u4e00\u6b21\u4e0e\u81ea\u7136\u7684\u4ea4\u4e92\u63a2\u7d22\uff0c\u4ee5\u6b64\u6765\u4e0d\u65ad\u5730\u53d1\u5c55\u8fdb\u6b65\u3002\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u5c31\u662f\u5728\u6a21\u4eff\u4eba\u7c7b\u7684\u8fd9\u79cd\u884c\u4e3a\uff1a\u667a\u80fd\u4f53\u5728\u4e8e\u73af\u5883\u7684\u4ea4\u4e92\u8fc7\u7a0b\u4e2d\u5b66\u4e60\u548c\u53d1\u73b0\u5176\u56e0\u679c\u5173\u7cfb\uff0c\u7136\u540e\u5229\u7528\u5b66\u5230\u7684\u56e0\u679c\u5173\u7cfb\u6765\u4f18\u5316\u81ea\u5df1\u7684\u7b56\u7565\u4ee5\u6307\u5bfc\u4e0b\u4e00\u6b65\u7684\u4ea4\u4e92\u3002\u6b63\u662f\u7531\u4e8e\u8fd9\u4e2a\u539f\u56e0\uff0c\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u53ef\u4ee5\u88ab\u89c6\u4e3a\u4e00\u79cd\u901a\u7528\u7684\u5b66\u4e60\u7b97\u6cd5\uff0c\u5728\u73b0\u5b9e\u751f\u6d3b\u4e2d\u6709\u7740\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u6bd4\u5982\uff1a\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u673a\u5668\u4eba\u3001\u751f\u7269\u533b\u836f\u3001\u5065\u5eb7\u533b\u7597\u3001\u63a8\u8350\u7cfb\u7edf\uff0c\u81ea\u52a8\u9a7e\u9a76\uff0c\u91d1\u878d\u3001\u793e\u4f1a\u5b66\u7b49\u7b49\u3002<\/span><\/section>\n
 <\/span><\/section>\n

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\u5927\u7eb2<\/span><\/strong><\/span><\/span><\/section>\n<\/h3>\n
    \n
  1. \n
    Introduction to Causal RL<\/section>\n<\/li>\n
      \n
    1. \n
      Brief Intro to RL and Causality<\/section>\n<\/li>\n
    2. \n
      Motivation<\/section>\n<\/li>\n
    3. \n
      Key Concepts<\/section>\n<\/li>\n
    4. \n
      Challenges<\/section>\n<\/li>\n
        \n
      1. \n
        Confoundings<\/section>\n<\/li>\n
      2. \n
        Counterfactuals<\/section>\n<\/li>\n
      3. \n
        Causal Representation Learning<\/section>\n<\/li>\n
      4. \n
        Artificial General Intelligence<\/section>\n<\/li>\n<\/ol>\n
      5. \n
        Applications<\/section>\n<\/li>\n
          \n
        1. \n
          Computer Vision<\/section>\n<\/li>\n
        2. \n
          Healthcare\/Medicine<\/section>\n<\/li>\n
        3. \n
          Self-driving<\/section>\n<\/li>\n
        4. \n
          Recommendation Systems<\/section>\n<\/li>\n<\/ol>\n<\/ol>\n
        5. \n
          Paper Reading<\/section>\n<\/li>\n
            \n
          1. \n
            Causality for RL [1-3]<\/section>\n<\/li>\n
          2. \n
            RL for Causality [4-5]<\/section>\n<\/li>\n<\/ol>\n
          3. \n
            Discussion<\/section>\n

            <\/section>\n<\/li>\n<\/ol>\n
            <\/p>\n


            <\/p>\n

            \u4e3b\u8bb2\u4eba\u4ecb\u7ecd<\/span><\/strong><\/span><\/section>\n
            \u9646\u8d85\u8d85\uff1a\u5251\u6865\u5927\u5b66\u5728\u8bfb\u535a\u58eb<\/span>\uff0c\u7814\u7a76\u65b9\u5411\u4e3a\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u3002<\/span><\/section>\n
            <\/span><\/section>\n
            \u5f20\u5353\u5a67\uff1a<\/span>\u6e05\u534e\u5927\u5b66\u5728\u8bfb\u535a\u58eb\uff0c\u7814\u7a76\u5174\u8da3\u662f\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u3002<\/span><\/section>\n

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

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

            \n
            <\/span><\/section>\n<\/h3>\n
            [1]  Dudik, M., Langford, J., Li, L. Doubly robust policy evaluation and learning. In Proceedings of 28th International Conference on Machine Learning. 2011.<\/span><\/section>\n
            [2] Bareinboim, E., Forney, A., Pearl, J. Bandits with Unobserved Confounders: A Causal Approach. In Proceedings of the 28th Annual Conference on Neural Information Processing Systems, 2015.<\/span><\/section>\n
            [3] Zhang, J., Bareinboim, E. Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach. In Proceedings of the 37th International Conference on Machine Learning. 2020.<\/span><\/section>\n
            [4] Khalil, Elias, et al. “Learning combinatorial optimization algorithms over graphs.” Advances in Neural Information Processing Systems. 2017.<\/span><\/section>\n
            [5] Zhu, Shengyu, Ignavier Ng, and Zhitang Chen. “Causal discovery with reinforcement learning.” arXiv preprint arXiv:1906.04477 (2019). <\/span><\/span><\/section>\n
            [6] Lu et al. “Deconfounding reinforcement learning in observational settings.” arXiv preprint arXiv:1812.10576<\/span><\/section>\n
            [7] Schoelkopf, Bernhard. “Causality for machinine learning.” arXiv preprint arXiv:1911.10500<\/span><\/section>\n
            [8] Buesing et al. “Woulda, coulda, shoulda: Counterfactually-guided policy search.” arXiv preprint arXiv:1811.06272<\/span><\/section>\n
            [9] de Haan et al. “Causal confusion in imitation learning.” arXiv preprint arXiv: 1905.11979<\/span><\/section>\n

            <\/section>\n

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            \u76f4\u64ad\u4fe1\u606f\u4e0e\u62a5\u540d\u65b9\u5f0f<\/strong><\/span><\/p>\n

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


            <\/section>\n

            \u76f4\u64ad\u65f6\u95f4\uff1a\u4eca\u5929<\/span><\/strong>\uff0811\u670829\u65e5\uff09 20:00-23:00<\/span><\/p>\n


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

            \u76f4\u64ad\u5730\u5740\uff1a<\/span><\/strong>\u96c6\u667a\u4ff1\u4e50\u90e8 B \u7ad9\u76f4\u64ad\u95f4<\/span><\/section>\n


            <\/p>\n

            \ud83d\udc40\u5173\u6ce8B\u7ad9\u4e3b\u64ad\u201c\u96c6\u667a\u4ff1\u4e50\u90e8\u201d<\/strong><\/strong><\/section>\n
            \u4e0d\u9519\u8fc7\u6bcf\u4e00\u573a\u96c6\u667a\u91cd\u78c5\u76f4\u64ad<\/strong><\/strong><\/section>\n


            <\/p>\n

            <\/section>\n
            \u76f4\u64ad\u5730\u5740\uff1a<\/strong><\/span>
            <\/section>\n
            https:\/\/live.bilibili.com\/8091531<\/strong><\/span><\/section>\n
            \u76f4\u64ad\u65f6<\/strong>\u95f4 \uff1a20:00-22:00<\/strong><\/section>\n


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            \u5173\u4e8e\u8bfb\u4e66\u4f1a\u5185\u5bb9\u4ecb\u7ecd\u7684\u66f4\u65b0<\/strong><\/span><\/p>\n

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

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            \u96c6\u667a\u4ff1\u4e50\u90e8\u8054\u5408\u667a\u6e90\u793e\u533a\u53d1\u8d77\u4e86\u56e0\u679c\u79d1\u5b66\u4e0eCausal AI\u8bfb\u4e66\u4f1a\u53d7\u5230\u4e86\u56e0\u679c\u79d1\u5b66\u9886\u57df\u4e00\u7ebf\u79d1\u7814\u5de5\u4f5c\u8005\u7684\u5e7f\u6cdb\u8ba4\u53ef\uff0c\u6211\u4eec\u4e5f\u6df1\u6df1\u7684\u611f\u53d7\u5230\u4e86\u9752\u5e74\u79d1\u5b66\u5de5\u4f5c\u8005\u63a8\u52a8\u8be5\u9886\u57df\u53d1\u5c55\u7684\u70ed\u60c5\u3002<\/span>\u76ee\u524d\u56e0\u679c\u79d1\u5b66\u4e0eCausal AI\u8bfb\u4e66\u4f1a\u5df2\u7ecf\u6709220+\u7684\u670b\u53cb\u62a5\u540d\uff0c\u5176\u4e2d\u7855\u535a\u7684\u6bd4\u4f8b\u63a5\u8fd180%\u3002<\/span><\/span><\/p>\n

            <\/span><\/p>\n<\/h2>\n

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            \u5728\u8bfb\u4e66\u4f1a\u4e2d\u7684\u53c2\u4e0e\u8005\u4ee5\u79d1\u7814\u5de5\u4f5c\u8005\u5c45\u591a\uff0c\u6e05\u534e\u5927\u5b66\u3001\u5317\u4eac\u5927\u5b66\u3001\u56fd\u9632\u79d1\u6280\u5927\u5b66\u3001\u6d59\u6c5f\u5927\u5b66\u3001\u590d\u65e6\u5927\u5b66\u3001\u4e2d\u5c71\u5927\u5b66\u7b49\u56fd\u5185\u9ad8\u6821\u7684\u5b66\u751f\u5c45\u591a\uff0c\u4e5f\u6709\u8bb8\u591a\u4e00\u7ebf\u4e92\u8054\u7f51\u5305\u62ec\u8c37\u6b4cX\u3001FackBook\u3001\u6ef4\u6ef4\u3001\u817e\u8baf\u3001\u963f\u91cc\u3001\u62fc\u591a\u591a\u7b49\u5927\u5382\u7684\u5de5\u7a0b\u5e08\u4e5f\u53c2\u4e0e\u5176\u4e2d\u3002<\/span><\/p>\n


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

            \u6b22\u8fce\u5927\u5bb6\u52a0\u5165\u5176\u4e2d\uff0c\u73b0\u5728\u52a0\u5165\u8bfb\u4e66\u4f1a\u7684\u6210\u5458\u5c06\u4f1a\u4f5c\u4e3a\u56e0\u679c\u793e\u533a\u7684\u79cd\u5b50\u7528\u6237\u957f\u671f\u8fd0\u8425\uff0c\u5c06\u53ef\u4ee5\u514d\u8d39\u4eab\u53d7\u96c6\u667a\u4ff1\u4e50\u90e8\u540e\u7eed\u56e0\u679c\u76f8\u5173\u4e3b\u9898\u7684\u8bfb\u4e66\u4f1a<\/strong>\uff0c\u5982\u679c\u4f60\u5fc3\u52a8\u4e86\uff0c\u5c31\u70b9\u51fb\u4e0b\u9762\u7684\u94fe\u63a5\u62a5\u540d\u5427~<\/span><\/p>\n

             <\/span><\/p>\n

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

            \u65f6\u95f4\uff1a<\/span><\/strong>9\u670820\u65e5\u8d77\uff0c\u6bcf\u5468\u65e5\u665a19:00-21:00\uff0c\u6301\u7eed\u7ea62-3\u4e2a\u6708<\/span><\/section>\n
            \u6a21\u5f0f\uff1a<\/span><\/strong>\u7ebf\u4e0a\u95ed\u95e8\u8bfb\u4e66\u4f1a\uff1b\u6536\u8d39-\u9000\u6b3e\u7684\u4fdd\u8bc1\u91d1\u6a21\u5f0f\uff1b\u8bfb\u4e66\u4f1a\u6210\u5458\u8ba4\u9886\u89e3\u8bfb\u8bba\u6587<\/span><\/section>\n
            \u8d39\u7528\uff1a<\/span><\/strong>299\/\u4eba<\/span><\/section>\n

             <\/span><\/p>\n

            \u4e86\u89e3\u8bfb\u4e66\u4f1a\u5177\u4f53\u89c4\u5219\u3001\u62a5\u540d\u8bfb\u4e66\u4f1a\u8bf7\u70b9\u51fb\u4e0b\u65b9\u6587\u7ae0\uff1a<\/span><\/p>\n

            \u56e0\u679c\u79d1\u5b66\u4e0e Causal AI \u7cfb\u5217\u8bfb\u4e66\u4f1a | \u4f17\u5305\u51fa\u4e66<\/span><\/a><\/section>\n


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            \u76ee\u524d\u8bfb\u4e66\u4f1a\u5df2\u7ecf\u6709\u8d85\u8fc7130\u4f59\u4eba\u7684\u6d77\u5185\u5916\u9ad8\u6821\u79d1\u7814\u9662\u6240\u7684\u4e00\u7ebf\u79d1\u7814\u5de5\u4f5c\u8005\u4ee5\u53ca\u4e92\u8054\u7f51\u4e00\u7ebf\u4ece\u4e1a\u4eba\u5458\u53c2\u4e0e\uff0c\u5982\u679c\u4f60\u4e5f\u5bf9\u8fd9\u4e2a\u4e3b\u9898\u611f\u5174\u8da3\uff0c\u5c31\u5feb\u52a0\u5165\u6211\u4eec\u5427\uff01<\/span><\/p>\n


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            <\/section>\n

            \u9488\u5bf9\u8bfb\u4e66\u4f1a\u7684\u4e3b\u9898\uff0c\u7531\u53d1\u8d77\u4eba\u9f9a\u9e64\u626c\u8bbe\u7f6e\u597d\u4e86\u5185\u5bb9\u6846\u67b6\uff0c\u6bcf\u4e2a\u4e3b\u9898\u4e0b\u6709\u4e00\u4e2a\u8d1f\u8d23\u4eba\u6765\u8d1f\u8d23\u7ef4\u62a4\u7ec4\u7ec7\u76f8\u5173\u5185\u5bb9\uff0c\u76ee\u524d\u5df2\u7ecf\u5b9a\u597d\u7684\u5982\u56fe\u6240\u793a\uff0c\u6b22\u8fce\u5bf9\u4e3b\u9898\u611f\u5174\u8da3\u7684\u8054\u7cfb\u76f8\u5173\u8d1f\u8d23\u4eba\uff0c\u4ee5\u53ca\u6765\u8ba4\u9886\u76f8\u5173\u4e3b\u9898~<\/span>
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            \u63a8\u8350\u9605\u8bfb<\/strong><\/strong><\/span><\/p>\n

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            <\/section>\n

            \u56fe\u7075\u5956\u5f97\u4e3bJudea Pearl \u667a\u6e90\u5927\u4f1a\u6f14\u8bb2\uff1a\u4ece\u201c\u5927\u6570\u636e\u9769\u547d\u201d\u5230\u201c\u56e0\u679c\u9769\u547d\u201d<\/strong><\/a>
            <\/p>\n

            \u4e3a<\/a><\/strong>\u4e86\u7814\u7a76\u56e0\u679c\u5173\u7cfb\uff0c\u539f\u6765\u79d1\u5b66\u5bb6\u5728\u8fd9\u4e48\u591a\u65b9\u5411\u4e0a\u90fd\u6709\u5c1d\u8bd5<\/a><\/strong><\/p>\n

            \u56e0\u679c\u53d1\u73b0\uff1a\u5982\u4f55\u8ba9\u7b97\u6cd5\u6210\u4e3a\u590d\u6742\u7cfb\u7edf\u4e2d\u7684\u201c\u798f\u5c14\u6469\u65af\u201d\uff1f<\/strong><\/a>
            <\/p>\n

            \u56e0\u679c\u79d1\u5b66\uff1a\u8fde\u63a5\u7edf\u8ba1\u5b66\u3001\u673a\u5668\u5b66\u4e60\u4e0e\u81ea\u52a8\u63a8\u7406\u7684\u65b0\u5174\u4ea4\u53c9\u9886\u57df<\/strong><\/a>
            <\/p>\n

            \u56e0\u679c\u89c2\u5ff5\u65b0\u9769\u547d\uff1f\u4e07\u5b57\u957f\u6587\uff0c\u89e3\u8bfb\u590d\u6742\u7cfb\u7edf\u80cc\u540e\u7684\u6697\u56e0\u679c<\/strong><\/a><\/p>\n

            \u52a0\u5165\u96c6\u667a\uff0c\u4e00\u8d77\u590d\u6742\uff01<\/strong><\/span><\/a><\/section>\n


            <\/p>\n

            \n
            \n
            \n
            \n


            <\/p>\n

            \n


            <\/p>\n


            <\/p>\n

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

            \u96c6\u667a\u4ff1\u4e50\u90e8QQ\u7fa4\uff5c877391004<\/span><\/strong><\/p>\n

            \u5546\u52a1\u5408\u4f5c\u53ca\u6295\u7a3f\u8f6c\u8f7d\uff5cswarma@swarma.org
            <\/span><\/strong><\/p>\n

            \n

            \u25c6 <\/span>\u25c6 <\/span>\u25c6<\/span><\/span><\/strong><\/strong><\/h1>\n<\/section>\n

            \u641c\u7d22\u516c\u4f17\u53f7\uff1a\u96c6\u667a\u4ff1\u4e50\u90e8<\/span><\/strong><\/span><\/p>\n


            <\/p>\n

            \u52a0\u5165\u201c\u6ca1\u6709\u56f4\u5899\u7684\u7814\u7a76\u6240\u201d<\/span><\/strong><\/span><\/p>\n

            \n

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

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


            <\/p>\n


            <\/p>\n

            \ud83d\udc47\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u6765\u770b\u76f4\u64ad\uff5e<\/span><\/span><\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

            \u4eca\u665a8\u70b9\uff0c\u201c\u56e0\u679c\u79d1\u5b66\u4e0eCausal AI\u201d\u8bfb\u4e66\u4f1a\u5c06\u8fdb\u884c\u7b2c\u5341\u671f\u7684\u7ebf\u4e0a\u8bba\u6587\u5206\u4eab\uff0c\u4e3b\u9898\u662f\u201c\u56e0\u679c\u5f3a\u5316\u5b66\u4e60\u201d\uff0c\u5c06\u7531\u5251\u6865\u5927\u5b66\u5728\u8bfb\u535a\u58eb\u9646\u8d85\u8d85\u3001\u6e05\u534e\u5927\u5b66\u5728\u8bfb\u535a\u58eb\u5f20\u5353\u5a67\u6765\u8fdb\u884c\u5206\u4eab\uff0c\u672c\u6b21\u5185\u5bb9\u5c06\u5728\u96c6\u667a\u4ff1\u4e50\u90e8B\u7ad9\u76f4\u64ad\u3002 \u4e3b\u9898\u80cc\u666f\u7b80\u4ecb \u8fd1\u4e9b\u5e74\u6765\uff0c\u5728\u6e38\u620f\u9886\u57df\u5f3a\u5316\u5b66\u4e60\u53d6\u5f97\u4e86\u5de8\u5927\u7684\u8fdb\u5c55\uff0c\u5df2\u7ecf\u80fd\u591f\u6253\u8d25\u4eba\u7c7b\u6700\u9876\u7ea7\u7684\u73a9\u5bb6\u3002\u4f46\u5728\u73b0\u5b9e\u751f\u6d3b\u4e2d…<\/p>\n","protected":false},"author":1,"featured_media":22220,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"special":[],"_links":{"self":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/22222"}],"collection":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=22222"}],"version-history":[{"count":0,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/22222\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/media\/22220"}],"wp:attachment":[{"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=22222"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=22222"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=22222"},{"taxonomy":"special","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fspecial&post=22222"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}