272 search results - page 19 / 55 » Parallel Reinforcement Learning with Linear Function Approxi... |
ECAI
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
PKDD
2009
Springer
14 years 2 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...
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
NIPS
1994
13 years 8 months ago
1994
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to real-world problems. Unfortun...
ADCM
2006
13 years 7 months ago
2006
This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...