272 search results - page 9 / 55 » Parallel Reinforcement Learning with Linear Function Approxi... |
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
This paper investigates reinforcement learning (RL) in XCS. First, it formally shows that XCS implements a method of generalized RL based on linear approximators, in which the usu...
AIIDE
2006
13 years 9 months ago
2006
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
IAT
2003
IEEE
14 years 23 days ago
2003
IEEE
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
AI
1998
Springer
13 years 7 months ago
1998
Springer
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...