Sewall Wright Lecture Series

Given by

Judea Pearl

University of California, Los Angeles


October 25 1999, 3:30-5:30pm
October 26,1999, 3:00-5:00pm

Room 210, The Fields Institute

These two lectures will summarize concepts, principles, and mathematical tools that were found useful in applications involving causal reasoning. The principles are based on structural-model semantics, in which functional (or counterfactual) relationships, representing autonomous physical processes are the fundamental building blocks. This formal basis has given rise to symbolic calculi and graph-based algorithms that enable one to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, and form theories of causal understanding and causal speech.

Judea Pearl is Professor of Computer Science and Statistics and Director of the Cognitive Systems Laboratory at the University of California, Los Angeles. He is the author of Heuristics (1984), Probabilistic Reasoning in Intelligent Systems (1988), Causality (forthcoming), and close to 200 articles on various aspects of automated reasoning, learning and inference. Pearl is a member of the National Academy of Engineering, a Fellow of the IEEE and AAAI, and a recipient of the IJCAI Research Excellence Award in Artificial Intelligence (1999).


``Causal Diagrams for Empirical Research,''
Biometrika, Vol. 82, No. 4, 669-709, December 1995.

``Reasoning with cause and effect,''
Proceedings of IJCAI-99, pp. 1437--1449, Morgan Kaufmann, 1999.

``Probabilities of causation: Three counterfactual interpretations and their identification,''
January 1999. Forthcoming, Synthese.

``The Art and Science of Cause and Effect,''
Public Lecture, October 1996.
Epilogue to CAUSALITY: Models, Reasoning, and Inference (Cambridge University Press, Forthcoming January 2000).