Tractable First-Order Golog with Disjunctive Knowledge Bases

While based on the Situation Calculus, current implementations of the agent control language Golog typically avoid offering full first-order capabilities, but rather resort to the closed-world assumption for the sake of efficiency. On the other hand, realistic applications need to deal with incomplete world knowledge including disjunctive information. Recently Liu, Lakemeyer and Levesque proposed the logic of limited belief SL, which lends itself to efficient reasoning in incomplete first-order knowledge bases. In particular, SL defines levels of belief which limit reasoning by cases in a principled way. In this paper, we propose to apply SL-based reasoning in the context of a Golog system. Central to our approach is a new search operator that finds plans only within a fixed belief level k, and an iterative-deepening-style variant where instead of considering plans with increasing length, the belief level k is incremented in each cycle. Thus, not the shortest plans are preferred, but those which are the computationally cheapest to discover.