Decision-Theoretic Planning with Linguistic Terms in Golog

Stefan Schiffer, Alexander Ferrein

Abstract: In this paper we propose an extension of the action language GOLOG that integrates linguistic terms in non-deterministic argument choices and the reward function for decision-theoretic planning. It is often cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, specifying a reward function is not always easy, even for domain experts. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in GOLOG, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy fluents. In GOLOG's forward-search DT planning algorithm, these formulas are evaluated in order to find the agent's optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.