46 search results - page 1 / 10 » A Sparse Sampling Algorithm for Near-Optimal Planning in Lar... |
ML
2002
ACM
13 years 4 months ago
2002
ACM
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
CISS
2008
IEEE
13 years 11 months ago
2008
IEEE
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
AIPS
2011
12 years 8 months ago
2011
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
IJCAI
2007
13 years 6 months ago
2007
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
ICTAI
2000
IEEE
13 years 8 months ago
2000
IEEE
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...