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

Craig Boutilier, Ray Reiter, and Mikhail Soutchanski, University of Toronto; Sebastian Thrun, Carnegie Mellon University

This paper proposes 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, but it also provides an interpreter that---given a logical axiomatization of a domain---will determine the optimal completion of that program (viewed as an MDP). We demonstrate the utility of this model by describing results obtained in an office delivery robotics domain.

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