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ICML
2000
IEEE
14 years 5 months ago
Convergence Problems of General-Sum Multiagent Reinforcement Learning
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
Michael H. Bowling
LAMAS
2005
Springer
13 years 10 months ago
Multi-agent Relational Reinforcement Learning
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
ECAI
2010
Springer
13 years 5 months ago
The Dynamics of Multi-Agent Reinforcement Learning
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
Luke Dickens, Krysia Broda, Alessandra Russo
AI
2002
Springer
13 years 4 months ago
Multiagent learning using a variable learning rate
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Michael H. Bowling, Manuela M. Veloso
ATAL
2007
Springer
13 years 10 months ago
Theoretical advantages of lenient Q-learners: an evolutionary game theoretic perspective
This paper presents the dynamics of multiple reinforcement learning agents from an Evolutionary Game Theoretic (EGT) perspective. We provide a Replicator Dynamics model for tradit...
Liviu Panait, Karl Tuyls