JudeaPearl
The Book of Why 豆瓣
作者: Judea Pearl / Dana Mackenzie 出版社: Allen Lane 2018 - 5
A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence
"Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality--the study of cause and effect--on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
2018年11月17日 已读
科学法是贝叶斯定理的一次应用。因果图形式化因果结构,do算子对有向无环图中指向X的有向边全部切断。由于变量不能全部观测,用前门准则来控制无法观察到的混杂因素,与RCT目标一致;若变量集合Z相对于(X,Y)满足后门准则,则X到Y因果可识别。感觉这些都是对相关性不能解决以及解决起来复杂的问题透明优化。反事实算法则扩宽数据解答问题的范围,NIE形式化间接影响。结构因果模型很大的一个优点就是对于线性非线性函数、离散或连续变量都有效。作者太卖关子,前几章讲统计学史,旧故事很多,7-9章是干货。思路是经典宏观实践的,因果哲学讲得很浅。但是应用领域极为广泛,毕竟是对相关性大改良,文科也能用呐。不知道因果模型处理相互干涉和叠加态什么的会怎么样。可能要读Causality一书才能深刻了解本书数学化的严格证明。
AI Causality JudeaPearl Judea_Pearl Reason