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» Convergence and No-Regret in Multiagent Learning
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AAMAS
2007
Springer
13 years 8 months ago
Reaching pareto-optimality in prisoner's dilemma using conditional joint action learning
We consider a repeated Prisoner’s Dilemma game where two independent learning agents play against each other. We assume that the players can observe each others’ action but ar...
Dipyaman Banerjee, Sandip Sen
ATAL
2010
Springer
13 years 9 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
AI
2007
Springer
14 years 2 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...
ATAL
2006
Springer
14 years 10 days ago
Learning the task allocation game
The distributed task allocation problem occurs in domains like web services, the grid, and other distributed systems. In this problem, the system consists of servers and mediators...
Sherief Abdallah, Victor R. Lesser
ATAL
2006
Springer
14 years 10 days ago
Learning to commit in repeated games
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
Stéphane Airiau, Sandip Sen