Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision

Searching for the Actual Cause

Judea Pearl
UCLA

Wednesday, May 10, 2000
refreshments 4:05PM
talk begins 4:15PM
TCseq201, Lecture Hall B
http://robotics.stanford.edu/ba-colloquium/

Abstract

Many problems in troubleshooting, legal decisions, and natural language processing require one to identify the "actual cause" of an event in the context of a given scenario (as in: ``Socrates drinking hemlock was the actual cause of Socrates death.'') Following a brief review of counterfactuals and their structural semantics, I will propose a formal account of actual causation based on the notion of "sustenance" -- the capacity of the cause to sustain the effect despite certain "structural" changes in the model. I will show by examples how this account avoids problems associated with the counterfactual-dependence account of Lewis (1986) and how it can be used both in generating explanations of specific scenarios and in computing the probabilities that such explanations are in fact correct.

References

Parts of this talk are based on chapter 10 of CAUSALITY (Cambridge U. Press, 2000), on my IJCAI-99 Lecture (see http://www.cs.ucla.edu/~judea/) and on recent joint work with J. Halpern.

About the Speaker

Judea Pearl is a Professor of Computer Science and Statistics at UCLA where he is the Director of the Cognitive Systems Laboratory.

He received the B.S. degree in Electrical Engineering from the Technion, Haifa, Israel, in 1960; a Master degree in Physics from Rutgers University, New Brunswick, New Jersey, in 1965; and a Ph.D. degree in Electrical Engineering from the Polytechnic Institute of Brooklyn, Brooklyn, NY in 1965.

Before coming to UCLA, he worked at RCA Research Laboratories, Princeton, New Jersey, on superconductive storage devices and magnetic memory systems. He joined UCLA in 1970, and his current interests include: knowledge representation, probabilistic and causal reasoning, constraint processing, nonstandard logics, distributed computation, and learning .

Pearl has published close to 200 research articles and is the author of three books: Heuristics (1984), Probabilistic Reasoning in Intelligent Systems (1988), and Causality: Models, Reasoning and Inference (2000). He is a Member of the National Academy of Engineering, a Fellow of the IEEE and the AAAI, and a recipient of the IJCAI Research Excellence Award in Artificial Intelligence (1999).

bac-coordinators@cs.stanford.edu