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AAMAS
2005
Springer
14 years 1 months ago
Advice-Exchange Between Evolutionary Algorithms and Reinforcement Learning Agents: Experiments in the Pursuit Domain
This research aims at studying the effects of exchanging information during the learning process in Multiagent Systems. The concept of advice-exchange, introduced in (Nunes and Ol...
Luís Nunes, Eugénio C. Oliveira
ROBOCUP
2005
Springer
134views Robotics» more  ROBOCUP 2005»
14 years 1 months ago
Simultaneous Learning to Acquire Competitive Behaviors in Multi-agent System Based on Modular Learning System
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments. A typical example is a case of RoboCup...
Yasutake Takahashi, Kazuhiro Edazawa, Kentarou Nom...
ATAL
2009
Springer
14 years 2 months ago
Multiagent reinforcement learning: algorithm converging to Nash equilibrium in general-sum discounted stochastic games
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Natalia Akchurina
ATAL
2007
Springer
14 years 1 months ago
Advice taking in multiagent reinforcement learning
This paper proposes the β-WoLF algorithm for multiagent reinforcement learning (MARL) in the stochastic games framework that uses an additional “advice” signal to inform agen...
Michael Rovatsos, Alexandros Belesiotis
ATAL
2006
Springer
13 years 11 months ago
Learning the required number of agents for complex tasks
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
Sébastien Paquet, Brahim Chaib-draa