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ATAL
2008
Springer
13 years 9 months ago
Efficient multi-agent reinforcement learning through automated supervision
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
ECML
2004
Springer
14 years 1 months ago
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Pieter Jan't Hoen, Karl Tuyls
ATAL
2008
Springer
13 years 9 months ago
Switching dynamics of multi-agent learning
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Peter Vrancx, Karl Tuyls, Ronald L. Westra
ITSSA
2006
109views more  ITSSA 2006»
13 years 7 months ago
Gene Expression Analysis in Multi-Agent Environment
Abstract. This paper presents a multi-agent approach to gene expression analysis and illustrates the working steps using real dataset produced from a microarray experiment. The ana...
H. C. Lam, M. Vazquez, B. Juneja, Scott C. Fahrenk...
CORR
2000
Springer
92views Education» more  CORR 2000»
13 years 7 months ago
Predicting the expected behavior of agents that learn about agents: the CLRI framework
We describe a framework and equations used to model and predict the behavior of multi-agent systems (MASs) with learning agents. A difference equation is used for calculating the ...
José M. Vidal, Edmund H. Durfee