267 search results - page 8 / 54 » The Dynamics of Multi-Agent Reinforcement Learning |
129
Voted
NECO
2002
15 years 4 months ago
2002
We propose a modular reinforcement learning architecture for non-linear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic i...
157
Voted
ATAL
2006
Springer
15 years 8 months ago
2006
Springer
In many Multi-Agent Systems (MAS), agents (even if selfinterested) need to cooperate in order to maximize their own utilities. Most of the multi-agent learning algorithms focus on...
148
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ATAL
2009
Springer
15 years 11 months ago
2009
Springer
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
140
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PPSN
2004
Springer
15 years 10 months ago
2004
Springer
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
170
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AAMAS
2007
Springer
15 years 11 months ago
2007
Springer
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 that...