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TiMDPpoly: An Improved Method for Solving Time-Dependent MDPs

Rachelson, Emmanuel and Fabiani, Patrick and Garcia, Frédérick TiMDPpoly: An Improved Method for Solving Time-Dependent MDPs. (2009) In: International Conference on Tools with Artificial Intelligence - ICTAI 2009, 2009 - 2009 (United States).

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Official URL: http://dx.doi.org/10.1109/ICTAI.2009.52

Abstract

We introduce TMDPpoly, an algorithm designed to solve planning problems with durative actions, under probabilistic uncertainty, in a non-stationary, continuous-time context. Mission planning for autonomous agents such as planetary rovers or unmanned aircrafts often correspond to such time-dependent planning problems. Modeling these problems can be cast through the framework of Time-dependent Markov Decision Processes (TiMDPs). We analyze the TiMDP optimality equations in order to exploit their properties. Then, we focus on the class of piecewise polynomial models in order to approximate TiMDPs, and introduce several algorithmic contributions which lead to the TMDPpoly algorithm for TiMDPs. Finally, our approach is evaluated on an unmanned aircraft mission planning problem and on an adapted version of the well-known Mars rover domain.

Item Type:Conference or Workshop Item (Paper)
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Institut National de la Recherche Agronomique - INRA (FRANCE)
French research institutions > Office National d'Etudes et Recherches Aérospatiales - ONERA (FRANCE)
Other partners > Technical University of Crete (GREECE)
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Deposited On:21 Nov 2017 16:19

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