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» Rational and Convergent Learning in Stochastic Games
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AI
2002
Springer
13 years 4 months ago
Multiagent learning using a variable learning rate
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Michael H. Bowling, Manuela M. Veloso
ICML
1998
IEEE
14 years 5 months ago
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
Junling Hu, Michael P. Wellman
AI
2007
Springer
13 years 11 months ago
Competition and Coordination in Stochastic Games
Agent competition and coordination are two classical and most important tasks in multiagent systems. In recent years, there was a number of learning algorithms proposed to resolve ...
Andriy Burkov, Abdeslam Boularias, Brahim Chaib-dr...
TON
2008
139views more  TON 2008»
13 years 4 months ago
Stochastic learning solution for distributed discrete power control game in wireless data networks
Distributed power control is an important issue in wireless networks. Recently, noncooperative game theory has been applied to investigate interesting solutions to this problem. Th...
Yiping Xing, Rajarathnam Chandramouli
NIPS
2001
13 years 6 months ago
The Steering Approach for Multi-Criteria Reinforcement Learning
We consider the problem of learning to attain multiple goals in a dynamic environment, which is initially unknown. In addition, the environment may contain arbitrarily varying ele...
Shie Mannor, Nahum Shimkin