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CORR
1998
Springer

The Computational Complexity of Probabilistic Planning

9 years 1 months ago
The Computational Complexity of Probabilistic Planning
We examine the computational complexity of testing and nding small plans in probabilistic planning domains with both at and propositional representations. The complexity of plan evaluation and existence varies with the plan type sought; we examine totally ordered plans, acyclic plans, and looping plans, and partially ordered plans under three natural de nitions of plan value. We show that problems of interest are complete for a variety of complexity classes: PL, P, NP, co-NP, PP, NPPP , co-NPPP , and PSPACE. In the process of proving that certain planning problems are complete for NPPP , we introduce a new basic NPPP -complete problem, E-Majsat, which generalizes the standard Boolean satis ability problem to computations involving probabilistic quantities; our results suggest that the development of good heuristics for E-Majsat could be important for the creation of e cient algorithms for a wide variety of problems.
Michael L. Littman, Judy Goldsmith, Martin Mundhen
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 1998
Where CORR
Authors Michael L. Littman, Judy Goldsmith, Martin Mundhenk
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