139 search results - page 13 / 28 » Model-based function approximation in reinforcement learning |
ECAI
2008
Springer
15 years 1 months ago
2008
Springer
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...
ICMLA
2007
15 years 1 months ago
2007
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
ICRA
2007
IEEE
15 years 6 months ago
2007
IEEE
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
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COR
2008
14 years 12 months ago
2008
Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such c...
CORR
2010
Springer
14 years 12 months ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...