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» Reducing the complexity of multiagent reinforcement learning
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ATAL
2004
Springer
14 years 12 days ago
Bayesian Reinforcement Learning for Coalition Formation under Uncertainty
Research on coalition formation usually assumes the values of potential coalitions to be known with certainty. Furthermore, settings in which agents lack sufficient knowledge of ...
Georgios Chalkiadakis, Craig Boutilier
AAMAS
2007
Springer
14 years 1 months ago
Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
ATAL
2005
Springer
14 years 17 days ago
An integrated framework for adaptive reasoning about conversation patterns
We present an integrated approach for reasoning about and learning conversation patterns in multiagent communication. The approach is based on the assumption that information abou...
Michael Rovatsos, Felix A. Fischer, Gerhard Wei&sz...
MAGS
2010
81views more  MAGS 2010»
13 years 1 months ago
Task allocation learning in a multiagent environment: Application to the RoboCupRescue simulation
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, Patric...
CORR
2000
Springer
92views Education» more  CORR 2000»
13 years 6 months ago
Predicting the expected behavior of agents that learn about agents: the CLRI framework
We describe a framework and equations used to model and predict the behavior of multi-agent systems (MASs) with learning agents. A difference equation is used for calculating the ...
José M. Vidal, Edmund H. Durfee