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TSMC
2008
146views more  TSMC 2008»
15 years 6 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
CORR
2010
Springer
135views Education» more  CORR 2010»
15 years 6 months ago
Bounded Rationality, Strategy Simplification, and Equilibrium
It is frequently suggested that predictions made by game theory could be improved by considering computational restrictions when modeling agents. Under the supposition that player...
Hubie Chen
FLAIRS
2010
15 years 8 months ago
Applying Goal Driven Autonomy to a Team Shooter Game
Dynamic changes in complex, real-time environments, such as modern video games, can violate an agent's expectations. We describe a system that responds competently to such vi...
Hector Muñoz-Avila, David W. Aha, Ulit Jaid...
IJCAI
2001
15 years 7 months ago
Rational and Convergent Learning in Stochastic Games
This paper investigates the problem of policy learning in multiagent environments using the stochastic game framework, which we briefly overview. We introduce two properties as de...
Michael H. Bowling, Manuela M. Veloso
CORR
2008
Springer
115views Education» more  CORR 2008»
15 years 7 months ago
Playing With Population Protocols
Population protocols have been introduced as a model of sensor networks consisting of very limited mobile agents with no control over their own movement: A collection of anonymous ...
Olivier Bournez, Jérémie Chalopin, J...