A Selection-Mutation Model for Q-learning in Multi-Agent Systems

Proceedings of the International Conference on Autonomous Agents

Volumn 2, Issue , 2003, Pages 693-700

  Tuyls, Karl ^a   Verbeeck, Katja ^a   Lenaerts, Tom ^a  

^a Computational Modeling Lab ^*  (Belgium)

Author keywords

Multi Agent Systems; Reinforcement Learning; Replicator Dynamics

Indexed keywords

ENTROPY; FEEDBACK; FUNCTIONS; GAME THEORY; LEARNING ALGORITHMS; MARKOV PROCESSES; MATHEMATICAL MODELS; SOFTWARE AGENTS;

REINFORCEMENT LEARNING; REPLICATOR DYNAMICS;

MULTI AGENT SYSTEMS;

EID: 1142268235     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/860575.860687     Document Type: Conference Paper

References (14)

1. Börgers, T., Sarin, R., Learning Through Reinforcement and Replicator Dynamics. Journal of Economic Theory, Volume 77, Number 1, November 1997.
2. Gintis, C.M., Game Theory Evolving. Princeton University Press, June 2000.
3. Hofbauer, J., Sigmund, K., Evolutionary Games and Population Dynamics, Cambridge University Press, 1998.
4. A. Nowé and K. Verbeeck, Distributed Reinforcement learning, Loadbased Routing a case study, author=" A. Nowé and K. Verbeeck", Notes of the Neural, Symbolic and Reinforcement Methods for sequence Learning Workshop at ijcai99, 1999, Stockholm, Sweden.
5. Osborne J.O., Rubinstein A., A course in game theory. Cambridge, MA: MIT Press (1994).
6. Redondo, F.V., Game Theory and Economics, Cambridge University Press, (2001).
7. L. Samuelson, Evolutionary Games and Equilibrium Selection, MIT Press, Cambridge, MA, 1997.
8. Schneider, T.D., Evolution of biological information, journal of NAR, volume 28, pages 2794-2799, 2000.
9. Stauffer, D., Life, Love and Death: Models of Biological Reproduction and Aging. Institute for Theoretical physics, Köln, Euroland, 1999.
10. Sutton, R.S., Barto, A.G. : Reinforcement Learning: An introduction. Cambridge, MA: MIT Press (1998).
11. Tuyls, K., Lenaerts, T., Verbeeck, K., Maes, S. and Manderick, B, Towards a Relation Between Learning Agents and Evolutionary Dynamics. Proceedings of BNAIC 2002. KU Leuven, Belgium.
12. Tuyls, K. and Verbeeck, K., The Replicator Dynamics as a model for Q-learning in games. Technical Report CoMo/10/2002, Vrije Universiteit Brussel, Belgium.
13. Watkins, C. and Dayan, P., Q-learning. Machine Learning, 8(3):279-292, 1992.
14. Weibull, J.W., Evolutionary Game Theory, MIT Press, (1996).