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» Convergence and No-Regret in Multiagent Learning
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ICML
2010
IEEE
13 years 9 months ago
Convergence, Targeted Optimality, and Safety in Multiagent Learning
This paper introduces a novel multiagent learning algorithm, Convergence with Model Learning and Safety (or CMLeS in short), which achieves convergence, targeted optimality agains...
Doran Chakraborty, Peter Stone
COGSR
2011
109views more  COGSR 2011»
13 years 3 months ago
How groups develop a specialized domain vocabulary: A cognitive multi-agent model
We simulate the evolution of a domain vocabulary in small communities. Empirical data show that human communicators can evolve graphical languages quickly in a constrained task (P...
David Reitter, Christian Lebiere
ATAL
2008
Springer
13 years 10 months ago
Using adaptive consultation of experts to improve convergence rates in multiagent learning
In this paper we study the use of experts algorithms in a multiagent setting. In this paper we allow agents to use multiple experts and explore different experts algorithms that a...
Greg Hines, Kate Larson
ICML
2000
IEEE
14 years 9 months ago
Convergence Problems of General-Sum Multiagent Reinforcement Learning
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
Michael H. Bowling
ATAL
2007
Springer
14 years 2 months ago
Regret based dynamics: convergence in weakly acyclic games
Regret based algorithms have been proposed to control a wide variety of multi-agent systems. The appeal of regretbased algorithms is that (1) these algorithms are easily implement...
Jason R. Marden, Gürdal Arslan, Jeff S. Shamm...