Adaptation and Learning in Multi-Agent Systems
IJCAI' 95 Workshop, Montreal, Canada, August 21,1995.Proceedings., Lecture Notes in Computer Science 1042 - Lecture Notes in Artificial Intelligence
Erschienen am
27.02.1996
Beschreibung
InhaltsangabeAdaptation and learning in multi-agent systems: Some remarks and a bibliography.- Refinement in agent groups.- Opponent modeling in multi-agent systems.- A multi-agent environment for department of defense distribution.- Mutually supervised learning in multiagent systems.- A framework for distributed reinforcement learning.- Evolving behavioral strategies in predators and prey.- To learn or not to learn.- A user-adaptive interface agency for interaction with a virtual environment.- Learning in multi-robot systems.- Learn your opponent's strategy (in polynomial time)!.- Learning to reduce communication cost on task negotiation among multiple autonomous mobile robots.- On multiagent Q-learning in a semi-competitive domain.- Using reciprocity to adapt to others.- Multiagent coordination with learning classifier systems.
Produktsicherheitsverordnung
Hersteller:
Springer Verlag GmbH
juergen.hartmann@springer.com
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