1. CIG 2005: Colchester, Essex, UK

• Georgios N. Yannakakis, John Hallam:
  A Generic Approach for Generating Interesting Interactive Pac-Man Opponents.
  
• Peter Blackburn, Barry O'Sullivan:
  Building Reactive Characters for Dynamic Gaming Environments.
  
• Leslie Luthi, Mario Giacobini, Marco Tomassini:
  Synchronous and Asynchronous Network Evolution in a Population of Stubborn Prisoners.
  
• Jörg Denzinger, Chris Winder:
  Combining Coaching and Learning to Create Cooperative Character Behavior.
  
• Kenneth O. Stanley, Bobby D. Bryant, Risto Miikkulainen:
  Real-Time Evolution in the NERO Video Game (Winner of CIG 2005 Best Paper Award).
  
• Umberto Cerruti, Mario Giacobini, Ugo Merlone:
  A New Framework to Analyze Evolutionary 2 x 2 Symmetric Games.
  
• Jin-Hyuk Hong, Sung-Bae Cho:
  Evolving Reactive NPCs for the Real-Time Simulation Game.
  
• Kazutomo Shibahara, Nobuo Inui, Yoshiyuki Kotani:
  Adaptive Strategies of MTD-f for Actual Games.
  
• Bruno Bouzy, Guillaume Chaslot:
  Bayesian Generation and Integration of K-nearest-neighbor Patterns for 19x19 Go.
  
• Tristan Cazenave, Bernard Helmstetter:
  Combining Tactical Search and Monte-Carlo in the Game of Go.
  
• Nanlin Jin, Edward P. K. Tsang:
  Co-evolutionary Strategies for an Alternating-Offer Bargaining Problem.
  
• Jörg Denzinger, Kevin Loose, Darryl Gates, John W. Buchanan:
  Dealing with Parameterized Actions in Behavior Testing of Commercial Computer Games.
  
• Akihiro Kishimoto, Martin Müller:
  Dynamic Decomposition Search: A Divide and Conquer Approach and its Application to the One-Eye Problem in Go.
  
• Evangelos Papacostantis, Andries Petrus Engelbrecht, Nelis Franken:
  Coevolving Probabilistic Game Playing Agents using Particle Swarm Optimization Algorithm.
  
• Colin Frayn:
  An Evolutionary Approach to Strategies for the Game of Monopoly.
  
• Yngvi Björnsson, Markus Enzenberger, Robert C. Holte, Jonathan Schaeffer:
  Fringe Search: Beating A* at Pathfinding on Game Maps.
  
• Maria Fasli, Michael Michalakopoulos:
  Designing and Implementing E-market Games.
  
• Jelle R. Kok, Pieter Jan't Hoen, Bram Bakker, Nikos A. Vlassis:
  Utile Coordination: Learning Interdependencies Among Cooperative Agents.
  
• Jay Bradley, Gillian Hayes:
  Adapting Reinforcement Learning for Computer Games: Using Group Utility Functions.
  
• Abdennour El Rhalibi, Michael Burkey:
  A Hybrid AI System for Agent Adaptation in a First Person Shooter.
  
• Aliza Gold:
  Academic AI and Videogames: A Case Study of Incorporating Innovative Academic Research Into a Videogame Prototype.
  
• Michael Chung, Michael Buro, Jonathan Schaeffer:
  Monte Carlo Planning in RTS Games.
  
• Daniel Livingstone:
  Coevolution in Hierarchical AI for Strategy Games.
  
• Julian Togelius, Simon M. Lucas:
  Forcing Neurocontrollers to Exploit Sensory Symmetry Through Hard-wired Modularity in the Game of Cellz.
  
• Simon M. Lucas:
  Evolving a Neural Network Location Evaluator to Play Ms. Pac-Man.
  
• Peter I. Cowling:
  Board Evaluation For The Virus Game.
  
• David B. Fogel, Timothy J. Hays, Sarah L. Hahn, James Quon:
  Further Evolution of a Self-Learning Chess Program.
  
• Chris Miles, Sushil J. Louis:
  Case-Injection Improves Response Time for a Real-Time Strategy Game.
  

Posters

• Kenneth Chisholm, Donald Fleming:
  A Study of Machine Learning using the Game of Fox and Geese.
  
• Damien Devigne, Philippe Mathieu, Jean-Christophe Routier:
  Team of cognitive agents with a leader: how to let them acquire autonomy.
  
• Erfu Yang, Dongbing Gu:
  A Survey on Multiagent Reinforcement Learning Towards Multi-Robot Systems.
  
• Kevin Burns:
  Pared-down Poker: Cutting to the Core of Command and Control.
  
• Kevin Burns:
  On TRACS: Dealing with a Deck of Double-Sided Cards.
  
• Colin Fyfe:
  Incrementally Learned Subjectivist Probabilities in Games.
  
• Timo Steffens:
  Similarity-based Opponent Modelling using Imperfect Domain Theories.
  
• Haruhiro Yoshimoto, Rie Shigetomi, Hideki Imai:
  How to Protect Peer-to-Peer Online Games from Cheats.
  
• Gayle Leen, Colin Fyfe:
  Training an AI Player to play Pong Using the GTM.
  
• Jordan B. Pollack:
  Nannon: A Nano Backgammon for Machine Learning Research.