Inferring State Constraints for Domain-Independent Planning

Alfonso Gerevini, Lenhart Schubert

We describe some new preprocessing techniques that enable faster domain-independent planning. The first set of techniques is aimed at inferring state constraints from the structure of planning operators and the initial state. Our methods consist of generating hypothetical state constraints by inspection of operator effects and preconditions, and checking each hypothesis against all operators and the initial conditions. Another technique extracts (supersets of) predicate domains from sets of ground literals obtained by Graphplan-like forward propagation from the initial state. Our various techniques are implemented in a package called DISCOPLAN. We show preliminary results on the effectiveness of adding computed state constraints and predicate domains to the specification of problems for SAT-based planners such as SATPLAN or MEDIC. The results suggest that large speedups in planning can be obtained by such automated methods, potentially obviating the need for adding hand-coded state constraints.


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