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  Unifying STRIPS and SAT with BLACKBOX

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by Henry Kautz, Bart Selman
http://ic-www.arc.nasa.gov/ic/people/frank/kautz.blackbox.cp98.FINAL.ps
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Abstract:

The blackbox planning system unifies the plan graph approach to STRIPS planning (Blum and Furst 1995) with the planning as satisfiability framework (Kautz and Selman 1992). We show that STRIPS problems can be directly translated into SAT and efficiently solved using new randomized systematic solvers. We also demonstrate that polynomial-time constraint propagation on the encoded problem instance provides a powerful complement to the "mutex" propagation algorithms that work directly on the plan graph. Overview It has often been observed that the classical AI planning problem (that is, planning with complete and certain

Citations

1397 STRIPS: A new approach in the application of theorem proving to problem solving – Fikes, Nilsson - 1971
1224 Some philosophical problems from the standpoint of arti cial intelligence – McCarthy, Hayes - 1969
740 Fast Planning Through Planning Graph Analysis – Blum, Furst - 1997
579 Planning for conjunctive goals – Chapman - 1987
432 Pushing the envelope: Planning propositional logic, and stochastic search – Kautz, Selman - 1996
278 Planning as satisfiability – Kautz, Selman - 1992
221 Boosting combinatorial search through randomization – Gomes, Selman, et al. - 1998
103 Automatic SAT-compilation of planning problems – Ernst, Millstein, et al. - 1997
73 Using temporal logic to control search in a forward chaining planner – Bacchus, Kabanza - 1995
63 Inferring state constraints for domain-independent planning – Gerevini, Schubert - 1998
49 Noise strategies for local search – Selman, Kautz, et al. - 1994
45 PDDL – The Planning Domain Definition Language – McDermott - 1998
9 The role of domainspecific axioms in the planning as satisfiability framework – Kautz, Selman - 1998
8 Min and Anbulagan – Li - 1997
3 The automatic inference of state invariants in TIM. Forthcoming – Fox, Long - 1998
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