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CEEMAS
2003
Springer
13 years 10 months ago
On a Dynamical Analysis of Reinforcement Learning in Games: Emergence of Occam's Razor
Modeling learning agents in the context of Multi-agent Systems requires an adequate understanding of their dynamic behaviour. Usually, these agents are modeled similar to the diļ¬...
Karl Tuyls, Katja Verbeeck, Sam Maes
ANOR
2005
80views more  ANOR 2005»
13 years 5 months ago
Entropic Penalties in Finite Games
The main objects here are finite-strategy games in which entropic terms are subtracted from the payoffs. After such subtraction each Nash equilibrium solves an explicit, unconstra...
Sjur Didrik Flåm, E. Cavazzuti
ATAL
2009
Springer
13 years 11 months ago
State-coupled replicator dynamics
This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate ...
Daniel Hennes, Karl Tuyls, Matthias Rauterberg
AAMAS
2007
Springer
13 years 11 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...
JMLR
2008
92views more  JMLR 2008»
13 years 5 months ago
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
This paper presents the dynamics of multiple learning agents from an evolutionary game theoretic perspective. We provide replicator dynamics models for cooperative coevolutionary ...
Liviu Panait, Karl Tuyls, Sean Luke