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» Asymmetric Multiagent Reinforcement Learning
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ATAL
2009
Springer
14 years 2 months ago
Stronger CDA strategies through empirical game-theoretic analysis and reinforcement learning
We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
L. Julian Schvartzman, Michael P. Wellman
AAAI
1998
13 years 9 months ago
Tree Based Discretization for Continuous State Space Reinforcement Learning
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
William T. B. Uther, Manuela M. Veloso
AI
1999
Springer
13 years 7 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
CEEMAS
2003
Springer
14 years 23 days 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
ATAL
2010
Springer
13 years 8 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah