SRL2004: Statistical Relational Learning and
its Connections to Other Fields

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 		Relations, generalizations and the reference-class problem: A logic programming / Bayesian perspective

David Poole
Dept of Computer Science
University of British Columbia

Logic programs provide a rich language to specify the interdependence between relations. There has been much success with inductive logic programming finding relationships from data. There has also been considerable success with Bayesian learning. However there is a large conceptual gap in that inductive logic programming does not have any statistics. This talk will explore how to get statistics from data. This problem is known as the reference-class problem. This talk will explore the combination of logic programming and hierarchical Bayesian models as a solution to the reference class problem.

This is joint work with Michael Chiang.