Forming Beliefs about a Changing World

Causal Reasoning and Uncertainty Management

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 12

Causal Reasoning

The situation calculus is a popular technique for reasoning about action and change. However, its restriction to a first-order syntax and pure deductive reasoning makes it unsuitable in many contexts. In particular, we often face uncertainty, due either to lack of knowledge or to some probabilistic aspects of the world. While attempts have been made to address aspects of this problem, most notably using nonmonotonic reasoning formalisms, the general problem of uncertainty in reasoning about action has not been fully dealt with in a logical framework. In this paper we present a theory of action that extends the situation calculus to deal with uncertainty. Our framework is based on applying the random-worlds approach of [BGHK94] to a situation calculus ontology, enriched to allow the expression of probabilistic action effects. Our approach is able to solve many of the problems imposed by incomplete and probabilistic knowledge within a unified framework. In particular, we obtain a default Markov property for chains of actions, a derivation of conditional independence from irrelevance, and a simple solution to the frame problem.