Planning for Concurrent Durative Uncertain Actions
Overview
Probabilistic planning problems are often modeled as Markov decision processes (MDPs), which assume that a single action is executed per decision epoch and that actions take unit time. However, in the real world it is common to execute several actions in parallel, and the durations of these actions may differ. We develop extensions to MDPs that incorporate these features. In particular, we propose the model of Concurrent MDPs, which allows simultaneous execution of multiple unit-duration actions at a time point. We extend this to handle concurrent durative actions with deterministic as well as stochastic durations.We release the code for our COMDP solver described in the AAAI'04 paper. Please download it here.
Publications
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Planning with Durative Actions in Stochastic Domains Mausam and Daniel S. Weld Journal of Artificial Intelligence Research, 2008. Journal Article (PDF) |
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Challenges for Temporal Planning with Uncertain Durations Mausam and Daniel S. Weld International Conference on Automated Planning and Scheduling, 2006. Poster (PDF) |
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Probabilistic Temporal Planning with Uncertain Durations Mausam and Daniel S. Weld AAAI Conference on Artificial Intelligence, 2006. Full Paper (PDF) |
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Concurrent Probabilistic Temporal Planning Mausam and Daniel S. Weld International Conference on Automated Planning and Scheduling, 2005. Full Paper |
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Solving Concurrent Markov Decision Processes Mausam and Daniel S. Weld AAAI Conference on Artificial Intelligence, 2004. Full Paper (PDF) |