210 search results - page 10 / 42 » An analysis of reinforcement learning with function approxim... |
105
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ECML
2004
Springer
15 years 5 months ago
2004
Springer
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
103
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GECCO
2004
Springer
15 years 5 months ago
2004
Springer
This paper introduces a gradient-based reward prediction update mechanism to the XCS classifier system as applied in neuralnetwork type learning and function approximation mechani...
ICRA
2009
IEEE
15 years 6 months ago
2009
IEEE
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
PKDD
2009
Springer
15 years 6 months ago
2009
Springer
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...
AAAI
2008
15 years 2 months ago
2008
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...