Die Liste enthält einfach alle Artikel, die ich mir zum Thema näher angeschaut habe. Die Auswahl ist z.T. recht zufällig. In den meisten Fällen werden aber Agenten beschrieben, die sich in einfachen, simulierten Umwelten bewegen.
Chora, A. (2001). Embodied Cognitive Science, Intelligent Behavior Control, Machine Learning, Soft Computing and FPGA Integration: Towards Fast, Cooperative and Adversial Robot Team (RoboCup). GMD Report Nr. 136. Sankt Augustin, GMD – Forschungszentrum Informationstechnik.
Davidsson, P. (1997). Learning by Linear Anticipation in Multi-Agent Systems. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 62-72.
Davies, W. & Edwards, P. (1997). The Communication of Inductive Inferences. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 221-241.
Friedrich, H., Kaiser, M., Rogalla, O. & Dillmann, R. (1997). Learning and Communication in Multi-Agent Systems. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 259-275.
Friedrich, H., Rogalla, O. & Dillmann, R. (1998). Propagation of action knowledge in multi-agent systems.: In Proceedings of the 9th IFAC Symposium on Information Control in Manufacturing (INCOM`98). Nancy.
Haynes, T., Lau, K. & Sen, S. (1996). Learning Cases To Compliment Rules For Conflict Resolution In Multiagent Systems.: AAAI Spring Symposium on Adaptation, Coevolution, and Learning in Multiagent Systems.
Ho, F. & Kamel, M. (1998). Learning Coordination Strategies for Cooperative Multiagent Systems. Machine Learning 33: 155-177.
Jim, K.-C. & Giles, C. L. (2000). Talking Helps: Evolving Communicating Agents for the Predator-Prey Pursuit Problem. Artificial Life 6(3): 237-254.
Lacey, N., Nakate, K. & Lee, M. (1997). Investigating the Effects of Explicit Epistemology on a Distributed Learning System. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 276-292.
Nadella, R. & Sen, S. (1997). Correlating Internal Parameters and External Performance: Learning Soccer Agents. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 137-150.
Ono, N. & Fukumoto, K. (1997). A Modular Approach to Multi-agent Reeinforcement Learning. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 25-39.
Plaza, E., Arcos, J. L. & MartÃn, F. (1997). Cooperative Case-Based Reasoning. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 180-201.
Potter, M. A., Meeden, L. A. & Schultz, A. C. (2001). Heterogeneity in the Coevolved Behaviors of Mobile Robots: The Emergence of Specialists.: Proceedings of The Seventeenth International Conference on Artificial Intelligence, August 4-10, 2001, Seattle, Washington, USA, Morgan Kaufmann: 1337-1343.
Reali Costa, A. H. & Veloso, M. (2000). Multi-Agent Learning of When to Communicate. In: Barros, L. N., et al.: International Joint Conference IBERAMIA’2000 and SBIA’2000, Workshop Proceedings, Meeting on Multi-Agent Collaborative and Adversarial Perception, Planning, Execution, and Learning: 169-174.
Schmidhuber, J. & Zhao, J. (1997). Multi-Agent Learning with the Success-Story Algorithm. In: Weiss, G.: Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer. 1237: 82-93.
Stone, P. & Veloso, M. (2000). Multiagent Systems: A Survey from a Machine Learning Perspective. Autonomous Robots 8(3): 345-383.
Weiss, G., Ed. (1997). Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments. Lecture Notes in Computer Science, Artificial Intelligence. Berlin, Springer.
Links
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