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ECML
2004
Springer
15 years 5 months ago
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Pieter Jan't Hoen, Karl Tuyls
TSMC
2008
146views more  TSMC 2008»
14 years 11 months ago
Decentralized Learning in Markov Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Peter Vrancx, Katja Verbeeck, Ann Nowé
89
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INFSOF
2008
90views more  INFSOF 2008»
14 years 11 months ago
JADE: A software framework for developing multi-agent applications. Lessons learned
Since a number of years agent technology is considered one of the most innovative technologies for the development of distributed software systems. While not yet a mainstream appr...
Fabio Bellifemine, Giovanni Caire, Agostino Poggi,...
ICML
2003
IEEE
16 years 12 days ago
Learning To Cooperate in a Social Dilemma: A Satisficing Approach to Bargaining
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
Jeff L. Stimpson, Michael A. Goodrich
FLAIRS
2003
15 years 29 days ago
Distributed Knowledge Representation in Neural-Symbolic Learning Systems: A Case Study
Neural-symbolic integration concerns the integration of symbolic and connectionist systems. Distributed knowledge representation is traditionally seen under a purely symbolic pers...
Artur S. d'Avila Garcez, Luís C. Lamb, Krys...