5 search results - page 1 / 1 » Using Bisimulation for Policy Transfer in MDPs |
AAAI
2010
13 years 6 months ago
2010
Knowledge transfer has been suggested as a useful approach for solving large Markov Decision Processes. The main idea is to compute a decision-making policy in one environment and...
RAS
2010
13 years 2 months ago
2010
Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration b...
AAAI
1997
13 years 5 months ago
1997
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
AAAI
2006
13 years 5 months ago
2006
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
UAI
1998
13 years 5 months ago
1998
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 app...