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AAMAS
2002
Springer
11 years 7 months ago
Multiagent Learning for Open Systems: A Study in Opponent Classification
Abstract. Open systems are becoming increasingly important in a variety of distributed, networked computer applications. Their characteristics, such as agent diversity, heterogenei...
Michael Rovatsos, Gerhard Weiß, Marco Wolf
TSMC
2008
229views more  TSMC 2008»
11 years 7 months ago
A Comprehensive Survey of Multiagent Reinforcement Learning
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
Lucian Busoniu, Robert Babuska, Bart De Schutter
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
11 years 9 months ago
Towards incremental social learning in optimization and multiagent systems
Social learning is a mechanism that allows individuals to acquire knowledge from others without incurring the costs of acquiring it individually. Individuals that learn socially c...
Marco Antonio Montes de Oca, Thomas Stützle
ATAL
2010
Springer
11 years 9 months ago
Evolving policy geometry for scalable multiagent learning
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
IJCAI
2003
11 years 9 months ago
Simultaneous Adversarial Multi-Robot Learning
Multi-robot learning faces all of the challenges of robot learning with all of the challenges of multiagent learning. There has been a great deal of recent research on multiagent ...
Michael H. Bowling, Manuela M. Veloso
ATAL
2006
Springer
11 years 10 months ago
Selecting informative actions improves cooperative multiagent learning
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
Liviu Panait, Sean Luke
ATAL
2008
Springer
11 years 10 months ago
MB-AIM-FSI: a model based framework for exploiting gradient ascent multiagent learners in strategic interactions
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Doran Chakraborty, Sandip Sen
ATAL
2008
Springer
11 years 10 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...
ARGMAS
2006
Springer
11 years 11 months ago
Arguments and Counterexamples in Case-Based Joint Deliberation
Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...
Santiago Ontañón, Enric Plaza
GECCO
2010
Springer
212views Optimization» more  GECCO 2010»
12 years 24 days ago
Generative and developmental systems
This paper argues that multiagent learning is a potential “killer application” for generative and developmental systems (GDS) because key challenges in learning to coordinate ...
Kenneth O. Stanley
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