GraphMDP: A New Decomposition Tool for Solving Markov Decision Processes
Résumé
In this paper, we present a new tool for solving weakly-coupled Markov Decision Processes using decomposition techniques. Using a predefined partition of the 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 by combining 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 implantation of our tool.