Multi-Contributor Causal Structures for Planning: A Formalization and Evaluation

Explicit causal structure representations have been widely used in classical planning systems to guide a variety of aspects of planning, including plan generation, modification and generalization. For the most part, these representations were limited to single-contributor causal structures. Although widely used, single-contributor causal structures have several limitations in handling partially ordered and partially instantiated plans. Specifically they are (i) incapable of exploiting redundancy in the plan causal structure and (ii) force premature commitment to individual contributors thereby causing unnecessary backtracking. In this paper, we study multi-contributor causal structures as a way of overcoming these limitations. We will provide a general formulation for multi-contributor causal links, and explore the properties of several special classes of this formulation. We will then describe two planning algorithms -MP and MP-I -that use multi-contributor causal links to organize their search for plans. We will describe empirical studies demonstrating the advantages of MP and MP-I over planners that use single contributor causal structures, and argue that they strike a more favorable balance in the tradeoff between search space redundancy and premature commitment to contributors. Finally, we will present a framework for justifying plans with respect to multi-contributor causal structures and describe its applications in plan modification and generalization. A preliminary version of this paper was presented at the 1st Intl. Conference on AI Planning Systems, College Park, MD, 20742, June 1992 [11]. Author’s e-mail address is [email protected]