63 search results - page 7 / 13 » Convergence and No-Regret in Multiagent Learning |
ATAL
2009
Springer
15 years 7 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...
103
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ICML
2003
IEEE
16 years 1 months ago
2003
IEEE
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...
109
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ICML
1998
IEEE
16 years 1 months ago
1998
IEEE
In this paper, we adopt general-sum stochastic games as a framework for multiagent reinforcement learning. Our work extends previous work by Littman on zero-sum stochastic games t...
94
Voted
TSMC
2008
15 years 7 days ago
2008
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...
ECAI
2008
Springer
15 years 2 months ago
2008
Springer
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...