141 search results - page 18 / 29 » Fuzzy Kanerva-based function approximation for reinforcement... |
WSC
2008
14 years 11 days 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...
ICML
2000
IEEE
14 years 11 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...
GECCO
2006
Springer
14 years 1 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 11 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...
ISNN
2007
Springer
14 years 4 months ago
2007
Springer
Normal fuzzy CMAC neural network performs well because of its fast learning speed and local generalization capability for approximating nonlinear functions. However, it requires hu...