Judea Pearl 有关因果推断的书

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Causality: Models, Reasoning, and Inference
Judea Pearl (Author)

详见
http://www.amazon.com/Causality-Reasoning-Inference-Judea-Pearl/dp/0521773628

没读过，不知道好坏。作者不赖，贝叶斯网络的专家。 Causality.pdf (23.53 MB, 需要: 10 个论坛币)

2014-8-1 07:53:49 上传

因果推断
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关键词：Pearl Earl DEA ARL ear 网络

建议楼主把书名加在主题栏里，这样搜索起来会更方便。谢谢。

这本书是Judea Pearl 写的因果推断方面比较系统的书，值得研究因果关系方向的人一读！

谢谢分享！https://mp.weixin.qq.com/s?__biz=MzI3MTM5ODA0Nw==&mid=2247484058&idx=1&sn=0dfe92a0991294afba2514b137217a66&chksm=eac3276addb4ae7c6acbc6f9275bf8ad5dcefafab631b41905d9f78c01ae46ddde8b2d9e7b31&mpshare=1&scene=1&srcid=1106iA6FLNHdX7osqGpLIRfv&pass_ticket=sV6a5peO6mhc1fnqurlf%2BK04KkVFjl4VfJRSLFDrkKno87%2BlxY5mVja3547F8u2W#rd

这是该书的第一版，作者在2009年更新了第二版本。不知谁有该版本。以下是关于作者的简介：
朱迪亚·珀尔[size=15.008px]（[size=15.008px]英语：Judea Pearl[size=15.008px]，1936年[size=15.008px]－[size=15.008px]）是一名[size=15.008px]美国[size=15.008px]计算机科学家[size=15.008px]和[size=15.008px]哲学家[size=15.008px]，因其[size=15.008px]人工智能[size=15.008px]概率方法的杰出成绩和[size=15.008px]贝氏网络[size=15.008px]的研发而知名。2011年，他因通过概率和因果推理的算法研发在[size=15.008px]人工智能[size=15.008px]取得的杰出贡献而获得[size=15.008px]图灵奖[size=15.008px]。
[size=15.008px]以下是该书的页面信息：
[size=15.008px]http://bayes.cs.ucla.edu/BOOK-09/causality2-excerpts.htm
[size=15.008px]

[size=15.008px]以下是该书第二版的Perface
[size=15.008px]

It has been more than eight years since the first edition of this book presented readerswith the friendly face of causation and her mathematical artistry. The popular receptionof the book and the rapid expansion of the structural theory of causation call for a newedition to assist causation through her second transformation – from a demystified wonderto a commonplace tool in research and education. This edition (1) provides technicalcorrections, updates, and clarifications in all ten chapters of the original book, (2) addssummaries of new developments and annotated bibliographical references at the end of eachchapter, and (3) elucidates subtle issues that readers and reviewers have found perplexing,objectionable, or in need of elaboration. These are assembled into an entirely new chapter(11) which, I sincerely hope, clears the province of causal thinking from the last tracesof controversy.Teachers who have taught from this book before should find the revised edition morelucid and palatable, while those who have waited for scouts to carve the path will findthe road paved and tested. Supplementary educational material, slides, tutorials, andhomework can be found on my website, http://www.cs.ucla.edu/~judea/.My main audience remain the students: students of statistics who wonder whyinstructors are reluctant to discuss causality in class; students of epidemiology who wonderwhy elementary concepts such as confounding are so hard to define mathematically;students of economics and social science who question the meaning of the parametersthey estimate; and, naturally, students of artificial intelligence and cognitive science,who write programs and theories for knowledge discovery, causal explanations, andcausal speech.I hope that each of these groups will find the unified theory of causation presentedin this book to be both inspirational and instrumental in tackling new challenges in theirrespective fields.J. P.Los AngelesJuly 2008

不久的将来它会变成人工智能的圣经

经济学中的因果推断方法培训课程（国庆班）【赵西亮教授独家分享】

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