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ICML
2002
IEEE
14 years 8 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans
ICMLA
2007
13 years 9 months ago
Control of a re-entrant line manufacturing model with a reinforcement learning approach
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...
José A. Ramírez-Hernández, Em...
COR
2008
142views more  COR 2008»
13 years 7 months ago
Application of reinforcement learning to the game of Othello
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...
Nees Jan van Eck, Michiel C. van Wezel
JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
A Convergent Online Single Time Scale Actor Critic Algorithm
Actor-Critic based approaches were among the first to address reinforcement learning in a general setting. Recently, these algorithms have gained renewed interest due to their gen...
Dotan Di Castro, Ron Meir
CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 7 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná