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ORCIDAdaptive Agents and Multi-Agents Systems (AAMAS) 2001 / 2002
- Eduardo Alonso, Daniel Kudenko, Dimitar Kazakov:
Adaptive Agents and Multi-Agent Systems: Adaptation and Multi-Agent Learning. Lecture Notes in Computer Science 2636, Springer 2003, ISBN 3-540-40068-0
Learning, Co-operation, and Communication
- Enric Plaza
, Santiago Ontañón:
Cooperative Multiagent Learning. 1-17 - Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens:
Reinforcement Learning Approaches to Coordination in Cooperative Multi-agent Systems. 18-32 - Luís Nunes, Eugénio Oliveira:
Cooperative Learning Using Advice Exchange. 33-48 - Péter András, Gilbert Roberts, John Lazarus:
Environmental Risk, Cooperation, and Communication Complexity. 49-65 - Michael Rovatsos, Gerhard Weiß, Marco Wolf:
Multiagent Learning for Open Systems: A Study in Opponent Classification. 66-87 - Henry Brighton, Simon Kirby, Kenny Smith:
Situated Cognition and the Role of Multi-agent Models in Explaining Language Structure. 88-109
Emergence and Evolution in Multi-agent Systems
- Philippe De Wilde, Maria Chli, Luís Correia, Rita Almeida Ribeiro, Pedro Mariano, Vladimir Abramov, Jan Goossenaerts:
Adapting Populations of Agents. 110-124 - Luc Steels:
The Evolution of Communication Systems by Adaptive Agents. 125-140 - Gauthier Picard, Marie-Pierre Gleizes:
An Agent Architecture to Design Self-Organizing Collectives: Principles and Application. 141-158 - Paul Marrow, Cefn Hoile, Fang Wang, Erwin Bonsma:
Evolving Preferences among Emergent Groups of Agents. 159-173 - Sander van Splunter, Niek J. E. Wijngaards, Frances M. T. Brazier:
Structuring Agents for Adaptation. 174-186 - Heather Turner, Dimitar Kazakov:
Stochastic Simulation of Inherited Kinship-Driven Altruism. 187-201
Theoretical Foundations of Adaptive Agents
- José M. Vidal:
Learning in Multiagent Systems: An Introduction from a Game-Theoretic Perspective. 202-215 - Nicholas Lacey, Mark H. Lee:
The Implications of Philosophical Foundations for Knowledge Representation and Learning in Agents. 216-238 - Pedro Rafael Graça, Graça Gaspar:
Using Cognition and Learning to Improve Agents' Reactions. 239-259 - William T. B. Uther, Manuela M. Veloso:
TTree: Tree-Based State Generalization with Temporally Abstract Actions. 260-290 - Christopher H. Brooks, Edmund H. Durfee:
Using Landscape Theory to Measure Learning Difficulty for Adaptive Agents. 291-305 - Saso Dzeroski:
Relational Reinforcement Learning for Agents in Worlds with Objects. 306-322
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