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ML
1998
ACM
101views Machine Learning» more  ML 1998»
12 years 1 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
CEC
2007
IEEE
12 years 6 months ago
Double-deck elevator systems using Genetic Network Programming with reinforcement learning
Abstract-- In order to increase the transportation capability of elevator group systems in high-rise buildings without adding elevator installation space, double-deck elevator syst...
Jin Zhou, Lu Yu, Shingo Mabu, Kotaro Hirasawa, Jin...
CIG
2005
IEEE
12 years 7 months ago
Adapting Reinforcement Learning for Computer Games: Using Group Utility Functions
AbstractGroup utility functions are an extension of the common team utility function for providing multiple agents with a common reinforcement learning signal for learning cooperat...
Jay Bradley, Gillian Hayes
EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
12 years 8 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
ATAL
2009
Springer
11 years 11 months ago
Decentralized Learning in Wireless Sensor Networks
In this paper we use a reinforcement learning algorithm with the aim to increase the autonomous lifetime of a Wireless Sensor Network (WSN) and decrease latency in a decentralized...
Mihail Mihaylov, Karl Tuyls, Ann Nowé
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