17 search results - page 2 / 4 » Rational and Convergent Learning in Stochastic Games |
109
Voted
AI
2002
Springer
14 years 10 months ago
2002
Springer
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 ...
94
Voted
ICML
1998
IEEE
15 years 11 months ago
1998
IEEE
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...
77
Voted
AI
2007
Springer
15 years 4 months ago
2007
Springer
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 ...
86
Voted
TON
2008
14 years 10 months ago
2008
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...
104
Voted
NIPS
2001
14 years 11 months ago
2001
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...