mGPT: A Probabilistic Planner Based on Heuristic Search

Details mGPT: A Probabilistic Planner Based on Heuristic Search mGPT: A Probabilistic Planner Based on Heuristic Search

2011-09-09

arxiv.org/abs/1109.2153v1

Journal Of Artificial Intelligence Research, Volume 24, pages 933-944, 2005

Computer Science

Artificial Intelligence

Scientific paper

10.1613/jair.1688

We describe the version of the GPT planner used in the probabilistic track of the 4th International Planning Competition (IPC-4). This version, called mGPT, solves Markov Decision Processes specified in the PPDDL language by extracting and using different classes of lower bounds along with various heuristic-search algorithms. The lower bounds are extracted from deterministic relaxations where the alternative probabilistic effects of an action are mapped into different, independent, deterministic actions. The heuristic-search algorithms use these lower bounds for focusing the updates and delivering a consistent value function over all states reachable from the initial state and the greedy policy.

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