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.

• Type: Conference
• Year: 2000
• Where: AAAI
• Authors: Craig Boutilier, Raymond Reiter, Mikhail Soutchanski, Sebastian Thrun
• Keywords: AAAI 2000, Explicit Agent Programming, Frameworkfor Robot Programming, Intelligent Agents, Markov Decision Process