Reasoning with cause and effect

Authors:
Judea Pearl
Affiliations:
Cognitive Systems Laboratory, Computer Science Department, University of California, Los Angeles
Venue:
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Year:
1999

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Abstract

This paper summarizes concepts, principles, and tools that were found useful in applications involving causal modeling. The principles are based on structural-model semantics, in which functional (or counterfactual) relationships, representing autonomous physical processes are the fundamental building blocks. The paper presents the formal basis of this semantics, illustrates its application in simple problems and discusses its ramifications to computational and cognitive problems concerning causation.