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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Vydané v:	Artificial intelligence Ročník 147; číslo 1; s. 85 - 117
Hlavní autori:	Castellini, Claudio, Giunchiglia, Enrico, Tacchella, Armando
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.07.2003
Predmet:	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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Abstract	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.
AbstractList	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. (Original abstract) 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.
Author	Giunchiglia, Enrico Castellini, Claudio Tacchella, Armando
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Snippet	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...
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SubjectTerms	Artificial intelligence Concurrency Planning Planning under uncertainty SAT-based planning Satisfiability
Title	SAT-based planning in complex domains: Concurrency, constraints and nondeterminism
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