MAXPLAN: A New Approach to Probabilistic Planning

Classical arti cial intelligence planning techniques can operate in large domains but traditionally assume a deterministic universe. Operations research planning techniques can operate in probabilistic domains but break when the domains approach realistic sizes. maxplan is a new probabilistic planning technique that aims at combining the best of these two worlds. maxplan converts a planning instance into an E-Majsat instance, and then draws on techniques from Boolean satis ability and dynamic programming to solve the E-Majsat instance. E-Majsat is an NP-complete problem that is essentially a probabilistic version of Sat. maxplan performs as much as an order of magnitude better on some standard stochastic test problems than buridan|a state-of-the-art probabilistic planner|and scales better on one test problem than two algorithms based on dynamic programming.