Decision-Theoretic, High-level Agent Programming in the Situation Calculus

Craig Boutilier, Ray Reiter, Mikhail Soutchanski
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: cebly,reiter,

Sebastian Thrun
School of Computer Science
Carnegie Mellon University
Pittsburgh, PA 15213-3891

We propose a framework for robot programming which allows the seamless integration of explicit agent programming with decision-theoretic planning. Specifically, the DTGolog model allows one to partially specify a control program in a high-level, logical language, and provides an interpreter that, given a logical axiomatization of a domain, will determine the optimal completion of that program (viewed as a Markov decision process). We demonstrate the utility of this model with results obtained in an office delivery robotics domain.

To appear, AAAI-2000

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