Sciweavers

UAI
1998

Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems

13 years 5 months ago
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these approaches, a large, stochastic decision problem is divided into smaller pieces. The first approach builds a cache of policies for each part of the problem independently, and then combines the pieces in a separate, light-weight step. A second approach also divides the problem into smaller pieces, but informationis communicatedbetween the different problem pieces, allowing intelligent decisions to be made about which piece requires the most attention. Both approaches can be used to find optimal policies or approximately optimal policies with provable bounds. These algorithms also provide a framework for the efficient transfer of knowledge across problems that share similar structure.
Ronald Parr
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 1998
Where UAI
Authors Ronald Parr
Comments (0)