OTHER
G<font>raph</font>MDP: A NEW DECOMPOSITION TOOL FOR SOLVING MARKOV DECISION PROCESSES
Pierre Laroche
- Year
- 2001
- Citations
- 2
Abstract
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.
Keywords
Computer scienceMarkov decision processMarkov chainDecompositionPartition (number theory)GraphGraph partitionMathematical optimizationArtificial intelligenceMarkov process
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
OTHER
Open access📊 20,501 cites
Fractional Differential Equations
Igor Podlubný
2025
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991