Causality: Models, Reasoning, And Inference
by Judea Pearl /
2000 / English / DjVu
11.5 MB Download
Written by one of the pre-eminent researchers in the field, this
book provides a comprehensive exposition of modern analysis of
causation. It shows how causality has grown from a nebulous concept
into a mathematical theory with significant applications in the
fields of statistics, artificial intelligence, philosophy,
cognitive science, and the health and social sciences. Pearl
presents a unified account of the probabilistic, manipulative,
counterfactual and structural approaches to causation, and devises
simple mathematical tools for analyzing the relationships between
causal connections, statistical associations, actions and
observations. The book will open the way for including causal
analysis in the standard curriculum of statistics, artifical
intelligence, business, epidemiology, social science and economics.
Students in these areas will find natural models, simple
identification procedures, and precise mathematical definitions of
causal concepts that traditional texts have tended to evade or make
unduly complicated. This book will be of interest to professionals
and students in a wide variety of fields. Anyone who wishes to
elucidate meaningful relationships from data, predict effects of
actions and policies, assess explanations of reported events, or
form theories of causal understanding and causal speech will find
this book stimulating and invaluable. Professor of Computer Science
at the UCLA, Judea Pearl is the winner of the 2008 Benjamin
Franklin Award in Computers and Cognitive Science.
Written by one of the pre-eminent researchers in the field, this
book provides a comprehensive exposition of modern analysis of
causation. It shows how causality has grown from a nebulous concept
into a mathematical theory with significant applications in the
fields of statistics, artificial intelligence, philosophy,
cognitive science, and the health and social sciences. Pearl
presents a unified account of the probabilistic, manipulative,
counterfactual and structural approaches to causation, and devises
simple mathematical tools for analyzing the relationships between
causal connections, statistical associations, actions and
observations. The book will open the way for including causal
analysis in the standard curriculum of statistics, artifical
intelligence, business, epidemiology, social science and economics.
Students in these areas will find natural models, simple
identification procedures, and precise mathematical definitions of
causal concepts that traditional texts have tended to evade or make
unduly complicated. This book will be of interest to professionals
and students in a wide variety of fields. Anyone who wishes to
elucidate meaningful relationships from data, predict effects of
actions and policies, assess explanations of reported events, or
form theories of causal understanding and causal speech will find
this book stimulating and invaluable. Professor of Computer Science
at the UCLA, Judea Pearl is the winner of the 2008 Benjamin
Franklin Award in Computers and Cognitive Science.