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 /

This book contains selected and 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. The goal of the ALAMAS symposia, and this associated book, is to increase awareness and int...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Tuyls, Karl (Επιμελητής έκδοσης), Nowe, Ann (Επιμελητής έκδοσης), Guessoum, Zahia (Επιμελητής έκδοσης), Kudenko, Daniel (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
Σειρά:Lecture Notes in Computer Science, 4865
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • To Adapt or Not to Adapt – Consequences of Adapting Driver and Traffic Light Agents
  • Optimal Control in Large Stochastic Multi-agent Systems
  • Continuous-State Reinforcement Learning with Fuzzy Approximation
  • Using Evolutionary Game-Theory to Analyse the Performance of Trading Strategies in a Continuous Double Auction Market
  • Parallel Reinforcement Learning with Linear Function Approximation
  • Combining Reinforcement Learning with Symbolic Planning
  • Agent Interactions and Implicit Trust in IPD Environments
  • Collaborative Learning with Logic-Based Models
  • Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems
  • Bifurcation Analysis of Reinforcement Learning Agents in the Selten’s Horse Game
  • Bee Behaviour in Multi-agent Systems
  • Stable Cooperation in the N-Player Prisoner’s Dilemma: The Importance of Community Structure
  • Solving Multi-stage Games with Hierarchical Learning Automata That Bootstrap
  • Auctions, Evolution, and Multi-agent Learning
  • Multi-agent Reinforcement Learning for Intrusion Detection
  • Networks of Learning Automata and Limiting Games
  • Multi-agent Learning by Distributed Feature Extraction.