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Communication Dans Un Congrès Année : 2023

Heuristic Search for Multi-Objective Probabilistic Planning

Recherche heuristique pour la planification probabiliste multi-objectifs

Résumé

Heuristic search is a powerful approach that has successfully been applied to a broad class of planning problems, including classical planning, multi-objective planning, and probabilistic planning modelled as a stochastic shortest path (SSP) problem. Here, we extend the reach of heuristic search to a more expressive class of problems, namely multi-objective stochastic shortest paths (MOSSPs), which require computing a coverage set of non-dominated policies. We design new heuristic search algorithms MOLAO* and MOLRTDP, which extend well-known SSP algorithms to the multi-objective case. We further construct a spectrum of domain-independent heuristic functions differing in their ability to take into account the stochastic and multi-objective features of the problem to guide the search. Our experiments demonstrate the benefits of these algorithms and the relative merits of the heuristics.
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Dates et versions

hal-04019253 , version 1 (08-03-2023)

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  • HAL Id : hal-04019253 , version 1

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Dillon Z Chen, Felipe Trevizan, Sylvie Thiébaux. Heuristic Search for Multi-Objective Probabilistic Planning. AAAI Conference on Artificial Intelligence, AAAI, Feb 2023, Washington DC, United States. ⟨hal-04019253⟩
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