Abstract
Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal planning, is a relatively new area of research. The challenge is to replicate the success of modern temporal and probabilistic planners with domains that exhibit an interaction between time and uncertainty. We present a general framework for probabilistic temporal planning in which effects, the time at which they occur, and action durations are all probabilistic. This framework includes a search space that is designed for solving probabilistic temporal planning problems via heuristic search, an algorithm that has been tailored to work with it, and an effective heuristic based on an extension of the planning graph data structure. Prottle is a planner that implements this framework, and can solve problems expressed in an extension of PDDL.
Original language | English |
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Pages | 1181-1186 |
Number of pages | 6 |
Publication status | Published - 2005 |
Event | 20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05 - Pittsburgh, PA, United States Duration: 9 Jul 2005 → 13 Jul 2005 |
Conference
Conference | 20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05 |
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Country/Territory | United States |
City | Pittsburgh, PA |
Period | 9/07/05 → 13/07/05 |