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inria-00101093, version 1

A New Decomposition Technique for Solving Markov Decision Processes

Pierre Laroche () a1, Yann Boniface () b2, René Schott 34

Symposium on Applied Computing - SAC'2001 (2001) 5 p

Abstract: In this paper, we present a new tool for automatically solving Markov Decision Processes. Using a predefined partition o fthe MDP, a directed graph is built to decompose the global MDP into small local MDPs which are independently solved. An approximate solution for the global MDP is obtained using local solutions. Our approach has been tested on a mobile robotics application. It allows near-optimal solutions to be obtained in significantly reduced time. We also present preliminary results concerning a parallel implementation.

  • a –  UNIVERSITE DE METZ
  • b –  UNIVERSITE NANCY 2
  • 1:  Laboratoire d'Informatique Théorique et Appliquée (LITA (EA3097))
  • Université Paul Verlaine - Metz
  • 2:  CORTEX (INRIA Lorraine - LORIA)
  • INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)
  • 3:  Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
  • INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)
  • 4:  Institut Elie Cartan Nancy (IECN)
  • CNRS : UMR7502 – INRIA – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)
  • Domain : Computer Science/Other
  • Keywords : planning under uncertainty – markov decision process – decomposition – parallelism || plannification sous incertitude – mdp – parallélisme
  • Internal note : A01-R-107 || laroche01a
  • Comment : Colloque avec actes et comité de lecture. internationale.
 
  • inria-00101093, version 1
  • oai:hal.inria.fr:inria-00101093
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  • Submitted on: Tuesday, 26 September 2006 14:56:27
  • Updated on: Monday, 11 June 2007 15:37:31