61 search results - page 1 / 13 » Adaptive Importance Sampling with Automatic Model Selection ... |
AAAI
2008
13 years 6 months ago
2008
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
BMCBI
2005
13 years 4 months ago
2005
Background: Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many import...
IWANN
1999
Springer
13 years 8 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
DAGSTUHL
2008
13 years 6 months ago
2008
Abstract. In this chapter, we present a new interactive procedure for multiobjective optimization, which is based on the use of a set of value functions as a preference model built...