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» Analyzing Multi-agent Reinforcement Learning Using Evolution...
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AAMAS
2007
Springer
14 years 1 months ago
Networks of Learning Automata and Limiting Games
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...
Peter Vrancx, Katja Verbeeck, Ann Nowé
ATAL
2008
Springer
13 years 9 months ago
Analysis of an evolutionary reinforcement learning method in a multiagent domain
Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassa...
ECAL
2005
Springer
14 years 1 months ago
The Quantitative Law of Effect is a Robust Emergent Property of an Evolutionary Algorithm for Reinforcement Learning
An evolutionary reinforcement-learning algorithm, the operation of which was not associated with an optimality condition, was instantiated in an artificial organism. The algorithm ...
J. J. McDowell, Zahra Ansari
AAMAS
2007
Springer
14 years 1 months ago
Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game
Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
EVOW
2003
Springer
14 years 20 days ago
Exploring the T-Maze: Evolving Learning-Like Robot Behaviors Using CTRNNs
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
Jesper Blynel, Dario Floreano