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ATAL
2006
Springer
15 years 10 months ago
Learning to cooperate in multi-agent social dilemmas
In many Multi-Agent Systems (MAS), agents (even if selfinterested) need to cooperate in order to maximize their own utilities. Most of the multi-agent learning algorithms focus on...
Jose Enrique Munoz de Cote, Alessandro Lazaric, Ma...
CDC
2008
IEEE
142views Control Systems» more  CDC 2008»
16 years 1 months ago
Convergence of rule-of-thumb learning rules in social networks
— We study the problem of dynamic learning by a social network of agents. Each agent receives a signal about an underlying state and communicates with a subset of agents (his nei...
Daron Acemoglu, Angelia Nedic, Asuman E. Ozdaglar
AAMAS
2011
Springer
15 years 1 months ago
Using focal point learning to improve human-machine tacit coordination
We consider an automated agent that needs to coordinate with a human partner when communication between them is not possible or is undesirable (tacit coordination games). Specifi...
Inon Zuckerman, Sarit Kraus, Jeffrey S. Rosenschei...
INFORMATICALT
2006
88views more  INFORMATICALT 2006»
15 years 6 months ago
Improving the Performances of Asynchronous Algorithms by Combining the Nogood Processors with the Nogood Learning Techniques
Abstract. The asynchronous techniques that exist within the programming with distributed constraints are characterized by the occurrence of the nogood values during the search for ...
Ionel Muscalagiu, Vladimir Cretu
MATES
2009
Springer
16 years 1 months ago
Towards a Taxonomy of Decision Making Problems in Multi-Agent Systems
Abstract. Taxonomies in the area of Multi-Agent Systems (MAS) classify problems according to the underlying principles and assumptions of the agents’ abilities, rationality and i...
Christian Guttmann