What evolutionary game theory tells us about multiagent learning
type: Item
instance of: scholarly article
title: What evolutionary game theory tells us about multiagent learning
zbMATH Open document ID: 1168.68497
author: Karl Tuyls
author: Simon Parsons
published in: Artificial Intelligence
publication date: 2009-07-09T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 91A22
Mathematics Subject Classification ID: 91A26
zbMATH DE Number: 5576677
zbMATH Keywords: evolutionary game theory
zbMATH Keywords: replicator dynamics
zbMATH Keywords: multiagent learning
MaRDI profile type: Publication
full work available at URL: j.artint.2007.01.004
OpenAlex ID: W2083535091
cites work: Learning through reinforcement and replicator dynamics
cites work: Q4223194
cites work: Q4067388
cites work: Evolutionary Games and Population Dynamics
cites work: Q3040961
cites work: The Logic of Animal Conflict
cites work: Q4945845
cites work: If multi-agent learning is the answer, what is the question?
cites work: Machine Learning: ECML 2004
cites work: Q5844986
DOI: 10.1016/J.ARTINT.2007.01.004
description: scientific article; zbMATH DE number 5576677