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168
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AAMAS
2007
Springer
16 years 27 days 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...
175
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GECCO
2007
Springer
16 years 26 days ago
2007
Springer
Engineering design increasingly uses computer simulation models coupled with optimization algorithms to find the best design that meets the customer constraints within a time con...
179
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IWCMC
2006
ACM
16 years 20 days ago
2006
ACM
One important characteristic of wireless sensor networks is energy stringency. Constructing a connected dominating set (CDS) has been widely used as a topology control strategy to...
165
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AUSAI
2005
Springer
16 years 7 days ago
2005
Springer
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
207
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DIALM
2004
ACM
16 years 4 days ago
2004
ACM
Coping with mobility and dynamism is one of the biggest challenges in ad hoc networks. An essential requirement for such networks is a service that can establish communication ses...