Karl Tuyls, Ann Nowé, Zahia Guessoum, Daniel Kudenko (Eds.):
Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning, 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems, Revised Selected Papers.
Lecture Notes in Computer Science 4865 Springer 2008, ISBN 978-3-540-77947-6 
revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS),
editions 2005,
2006 and 2007,
held in Paris,
Brussels and Maastricht
- Ana L. C. Bazzan, Denise de Oliveira, Franziska Klügl, Kai Nagel:
To Adapt or Not to Adapt - Consequences of Adapting Driver and Traffic Light Agents.
1-14
- Bart van den Broek, Wim Wiegerinck, Bert Kappen:
Optimal Control in Large Stochastic Multi-agent Systems.
15-26
- Lucian Busoniu, Damien Ernst, Bart De Schutter, Robert Babuska:
Continuous-State Reinforcement Learning with Fuzzy Approximation.
27-43
- Kai Cai, Jinzhong Niu, Simon Parsons:
Using Evolutionary Game-Theory to Analyse the Performance of Trading Strategies in a Continuous Double Auction Market.
44-59
- Matthew Grounds, Daniel Kudenko:
Parallel Reinforcement Learning with Linear Function Approximation.
60-74
- Matthew Grounds, Daniel Kudenko:
Combining Reinforcement Learning with Symbolic Planning.
75-86
- Enda Howley, Colm O'Riordan:
Agent Interactions and Implicit Trust in IPD Environments.
87-101
- Michal Jakob, Jan Tozicka, Michal Pechoucek:
Collaborative Learning with Logic-Based Models.
102-116
- Steven de Jong, Karl Tuyls, Katja Verbeeck, Nico Roos:
Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems.
117-128
- Alessandro Lazaric, Jose Enrique Munoz de Cote, Fabio Dercole, Marcello Restelli:
Bifurcation Analysis of Reinforcement Learning Agents in the Selten's Horse Game.
129-144
- Nyree Lemmens, Steven de Jong, Karl Tuyls, Ann Nowé:
Bee Behaviour in Multi-agent Systems.
145-156
- Colm O'Riordan, Humphrey Sorensen:
Stable Cooperation in the N-Player Prisoner's Dilemma: The Importance of Community Structure.
157-168
- Maarten Peeters, Katja Verbeeck, Ann Nowé:
Solving Multi-stage Games with Hierarchical Learning Automata That Bootstrap.
169-187
- Steve Phelps, Kai Cai, Peter McBurney, Jinzhong Niu, Simon Parsons, Elizabeth Sklar:
Auctions, Evolution, and Multi-agent Learning.
188-210
- Arturo Servin, Daniel Kudenko:
Multi-agent Reinforcement Learning for Intrusion Detection.
211-223
- Peter Vrancx, Katja Verbeeck, Ann Nowé:
Networks of Learning Automata and Limiting Games.
224-238
- Michael Wurst:
Multi-agent Learning by Distributed Feature Extraction.
239-254
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