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Acting and Planning Using Operational Models

Abstract : The most common representation formalisms for planning are descriptive models. They abstractly describe what the actions do and are tailored for efficiently computing the next state(s) in a state transition system. But acting requires operational models that describe how to do things, with rich control structures for closed-loop online decision-making. Using descriptive representations for planning and operational representations for acting can lead to problems with developing and verifying consistency of the different models. We define and implement an integrated acting-and-planning system in which both planning and acting use the same operational models, which are written in a general-purpose hierarchical task-oriented language offering rich control structures. The acting component is inspired by the well-known PRS system, except that instead of being purely reactive, it can get advice from the planner. Our planning algorithm, RAE-plan, plans by doing Monte Carlo rollout simulations of the actor's operational models. Our experiments show significant benefits in the efficiency of the acting and planning system.
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Contributor : Malik Ghallab <>
Submitted on : Tuesday, January 15, 2019 - 1:25:51 PM
Last modification on : Thursday, June 10, 2021 - 3:06:37 AM
Long-term archiving on: : Tuesday, April 16, 2019 - 12:51:53 PM


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  • HAL Id : hal-01959110, version 1


Sunandita Patra, Malik Ghallab, Dana Nau, Paolo Traverso. Acting and Planning Using Operational Models. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Jan 2019, Honolulu, United States. ⟨hal-01959110⟩



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