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ORCID14th IJCAI 1995: Montréal, Québec, Canada - Adaption and Learning in Multi-Agent Systems
- Gerhard Weiß, Sandip Sen:
Adaption and Learning in Multi-Agent Systems, IJCAI'95 Workshop, Montréal, Canada, August 21, 1995, Proceedings. Lecture Notes in Computer Science 1042, Springer 1996, ISBN 3-540-60923-7
Introduction
- Gerhard Weiß:
Adaptation and Learning in Multi-Agent Systems: Some Remarks and a Bibliography. 1-21
Workshop Contributions
- Ciara Byrne, Peter Edwards
:
Refinement in Agent Groups. 22-39 - David Carmel, Shaul Markovitch:
Opponent Modeling in Multi-Agent Systems. 40-52 - Laurence Glicoes, Richard Staats, Michael N. Huhns:
A Multi-Agent Environment for Department of Defense Distribution. 53-84 - Claudia V. Goldman, Jeffrey S. Rosenschein:
Mutually Supervised Learning in Multiagent Systems. 85-96 - Pan Gu, Anthony B. Maddox:
A Framework for Distributed Reinforcement Learning. 97-112 - Thomas Haynes, Sandip Sen:
Evolving Beharioral Strategies in Predators and Prey. 113-126 - Anupam Joshi:
To Learn or Not do Learn. 127-139 - Britta Lenzmann, Ipke Wachsmuth:
A User-Adaptive Interface Agency for Interaction with a Virtual Environment. 140-151 - Maja J. Mataric:
Learning in Multi-Robot Systems. 152-163 - Yishay Mor, Claudia V. Goldman, Jeffrey S. Rosenschein:
Learn Your Opponent's Strategy (in Polynominal Time)! 164-176 - Takuya Ohko, Kazuo Hiraki, Yuichiro Anzai:
Learning to Reduce Communication Cost on Task Negotiation among Multiple Autonomous Mobile Robots. 177-190 - Tuomas Sandholm, Robert H. Crites:
On Multiagent Q-Learning in a Semi-Competitive Domain. 191-205 - Sandip Sen, Mahendra Sekaran:
Using Reciprocity to Adapt to Others. 206-217 - Sandip Sen, Mahendra Sekaran:
Multiagent Coordination with Learning Classifier Systems. 218-234
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