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24
Voted
COR
2008
13 years 7 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...
AAAI
1998
13 years 8 months ago
1998
In this paper, we describe methods for e ciently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boo...
AAMAS
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
ICMLA
2003
13 years 8 months ago
2003
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...