Heuristic Guidance Measures for Conformant Planning

Daniel Bryce and Subbarao Kambhampati

Scaling conformant planning is a problem that has received much attention of late. Many planners solve the problem as a search in the space of belief states, and some heuristic guidance techniques have been developed to estimate the distance between belief states. We claim that heuristic techniques in the past involved an ad hoc combination of classical planning heuristics and cardinality measures. We discuss how to derive heuristics systematically, with the help of planning graphs, such that the measures reflect the reachability of relevant states within belief states. To demonstrate these ideas we show how distances between belief states can be estimated by a set of reachability heuristics. We empirically evaluate their effectiveness within a conformant regression planner named CAltAlt.

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