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Concurrent probabilistic planning in the graphplan framework

Little, Iain; Thiebaux, Sylvie


We consider the problem of planning optimally in potentially concurrent probabilistic domains: actions have probabilistic effects and may execute in parallel under certain conditions; we seek a contingency plan that maximises the probability of reaching the goal. The Graphplan framework has proven to be highly successful at solving classical planning problems, but has not previously been applied to probabilistic planning in its entirety. We present an extension of the full framework to...[Show more]

CollectionsANU Research Publications
Date published: 2006
Type: Conference paper
Source: Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling


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