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

We propose a frameworkfor 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 highlevel, 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.

Authors

• Craig Boutilier Google Research
• and Mikhail Soutchanski University of Toronto; Sebastian Thrun

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