SAT-based planning in complex domains: Concurrency, constraints and nondeterminism

Planning as satisfiability is a very efficient technique for classical planning, i.e., for planning domains in which both the effects of actions and the initial state are completely specified. In this paper we present C - sat, a SAT-based procedure capable of dealing with planning domains having inc...

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Veröffentlicht in:Artificial intelligence Jg. 147; H. 1; S. 85 - 117
Hauptverfasser: Castellini, Claudio, Giunchiglia, Enrico, Tacchella, Armando
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.07.2003
Schlagworte:
Artificial intelligence
Concurrency
Planning
Planning under uncertainty
SAT-based planning
Satisfiability
SAT-based planning
Concurrency
Planning under uncertainty
Satisfiability
ISSN:0004-3702, 1872-7921
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Zusammenfassung:Planning as satisfiability is a very efficient technique for classical planning, i.e., for planning domains in which both the effects of actions and the initial state are completely specified. In this paper we present C - sat, a SAT-based procedure capable of dealing with planning domains having incomplete information about the initial state, and whose underlying transition system is specified using the highly expressive action language C . Thus, C - sat allows for planning in domains involving (i) actions which can be executed concurrently; (ii) (ramification and qualification) constraints affecting the effects of actions; and (iii) nondeterminism in the initial state and in the effects of actions. We first prove the correctness and the completeness of C - sat, discuss some optimizations, and then we present C - plan, a system based on C - sat. C - plan works on any C planning problem, but some optimizations have not been fully implemented yet. Nevertheless, the experimental analysis shows that SAT-based approaches to planning with incomplete information are viable, at least in the case of problems with a high degree of parallelism.
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ISSN:0004-3702
1872-7921
DOI:10.1016/S0004-3702(02)00375-2