| Author(s) |
Pierre Laroche ( )1, Yann Boniface ( )2, René Schott3, 4 |
| Research team(s) |
|
| Domain |
Computer Science/Other
|
| Title |
A New Decomposition Technique for Solving Markov Decision Processes |
| 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. |
| Full text language |
English |
|
| Publication date |
2001 |
| Audience |
international |
| Conference title |
Symposium on Applied Computing - SAC'2001 |
| Conference city |
Las Vegas, USA |
| Conference date |
2001 |
| Scientific editor(s) |
ACM |
| Commercial editor |
none |
| Pagination |
5 p |
|
| Keywords |
planning under uncertainty – markov decision process – decomposition – parallelism || plannification sous incertitude – mdp – parallélisme |
| Comment |
Colloque avec actes et comité de lecture. internationale. |
| Internal note |
A01-R-107 || laroche01a |