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PPSN
2004
Springer
14 years 1 months ago
Evolutionary Multi-agent Systems
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
Pieter Jan't Hoen, Edwin D. de Jong
ILP
2000
Springer
13 years 11 months ago
Using ILP to Improve Planning in Hierarchical Reinforcement Learning
Hierarchical reinforcement learning has been proposed as a solution to the problem of scaling up reinforcement learning. The RLTOPs Hierarchical Reinforcement Learning System is an...
Mark D. Reid, Malcolm R. K. Ryan
ICMLA
2010
13 years 5 months ago
Incremental Learning of Relational Action Rules
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Christophe Rodrigues, Pierre Gérard, C&eacu...
AAMAS
2002
Springer
13 years 7 months ago
Cooperative Learning Using Advice Exchange
Abstract. One of the main questions concerning learning in a Multi-Agent System's environment is: "(How) can agents benefit from mutual interaction during the learning pr...
Luís Nunes, Eugenio Oliveira
LAMAS
2005
Springer
14 years 1 months ago
An Overview of Cooperative and Competitive Multiagent Learning
Abstract Multi-agent systems (MASs) is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexiti...
Pieter Jan't Hoen, Karl Tuyls, Liviu Panait, Sean ...