Hindawi Publishing Corporation International Journal of Computer Games Technology Volume 2008, Article ID 432365, 18 pages doi:10.1155/2008/432365 Research Article A Hybrid Fuzzy ANN System for Agent Adaptation in a First Person Shooter Abdennour El Rhalibi and Madjid Merabti School of Computing and Mathematical Sciences, Liverpool John Moores University, James Parsons Building, Byrom Street, L3 3AF, Liverpool, UK Correspondence should be addressed to Abdennour El Rhalibi,
[email protected] Received 31 July 2007; Accepted 1 November 2007 Recommended by Kok Wai Wong The aim of developing an agent, that is able to adapt its actions in response to their effectiveness within the game, provides the basis for the research presented in this paper. It investigates how adaptation can be applied through the use of a hybrid of AI tech- nologies. The system developed uses the predefined behaviours of a finite-state machine and fuzzy logic system combined with the learning capabilities of a neural computing. The system adapts specific behaviours that are central to the performance of the bot (a computer-controlled player that simulates a human opponent) in the game with the paper’s main focus being on that of the weapon selection behaviour, selecting the best weapon for the current situation. As a development platform, the project makes use of the Quake 3 Arena engine, modifying the original bot AI to integrate the adaptive technologies. Copyright © 2008 A. El Rhalibi and M. Merabti. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.