141 search results - page 3 / 29 » CBR for State Value Function Approximation in Reinforcement ... |
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
PKDD
2009
Springer
14 years 15 days 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...
NN
2010
Springer
13 years 22 days ago
2010
Springer
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
AAAI
1998
13 years 7 months ago
1998
In this paper, we describe methods for e ciently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boo...