210 search results - page 14 / 42 » An analysis of reinforcement learning with function approxim... |
108
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NIPS
2008
15 years 1 months ago
2008
In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
105
Voted
ICCBR
2007
Springer
15 years 5 months ago
2007
Springer
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...
101
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NIPS
1996
15 years 1 months ago
1996
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
ECAI
2008
Springer
15 years 1 months ago
2008
Springer
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...
94
Voted
PKDD
2009
Springer
15 years 6 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...