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NIPS
1996
14 years 11 months ago
Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems
In cellular telephone systems, an important problem is to dynamically allocate the communication resource channels so as to maximize service in a stochastic caller environment. Th...
Satinder P. Singh, Dimitri P. Bertsekas
ATAL
2009
Springer
15 years 4 months ago
Learning of coordination: exploiting sparse interactions in multiagent systems
Creating coordinated multiagent policies in environments with uncertainty is a challenging problem, which can be greatly simplified if the coordination needs are known to be limi...
Francisco S. Melo, Manuela M. Veloso
ICML
2006
IEEE
15 years 10 months ago
Relational temporal difference learning
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Nima Asgharbeygi, David J. Stracuzzi, Pat Langley
IJCNN
2008
IEEE
15 years 4 months ago
A formula of equations of states in singular learning machines
Abstract— Almost all learning machines used in computational intelligence are not regular but singular statistical models, because they are nonidentifiable and their Fisher info...
Sumio Watanabe
CG
2000
Springer
15 years 2 months ago
Chess Neighborhoods, Function Combination, and Reinforcement Learning
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
Robert Levinson, Ryan Weber