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Learning Automata as a Basis for Multi Agent Reinforcement Learning.

Authors :
Tuyls, Karl
't Hoen, Pieter Jan
Sen, Sandip
Nowé, Ann
Verbeeck, Katja
Peeters, Maarten
Source :
Learning & Adaption in Multi-Agent Systems; 2006, p71-85, 15p
Publication Year :
2006

Abstract

In this paper we summarize some important theoretical results from the domain of Learning Automata. We start with single stage, single agent learning schema's, and gradually extend the setting to multi-stage multi agent systems. We argue that the theory of Learning Automata is an ideal basis to build multi agent learning algorithms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540330530
Database :
Supplemental Index
Journal :
Learning & Adaption in Multi-Agent Systems
Publication Type :
Book
Accession number :
32889215
Full Text :
https://doi.org/10.1007/11691839_3