210 search results - page 18 / 42 » An analysis of reinforcement learning with function approxim... |
121
Voted
ECML
2004
Springer
15 years 8 months ago
2004
Springer
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
115
Voted
WSC
2008
15 years 5 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
121
Voted
ICML
2000
IEEE
16 years 4 months ago
2000
IEEE
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
113
Voted
GECCO
2006
Springer
15 years 7 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...
139
Voted
AIIDE
2006
15 years 4 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...