C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Machine Learning
Machine learning techniques for FPS in Q3
Proceedings of the 2004 ACM SIGCHI International Conference on Advances in computer entertainment technology
Bayesian Imitation of Human Behavior in Interactive Computer Games
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
An evolutionary online adaptation method for modern computer games based on imitation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Imitation-based evolution of artificial players in modern computer games
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Real-time imitation-based adaptation of gaming behaviour in modern computer games
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Online behavior change detection in computer games
Expert Systems with Applications: An International Journal
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Modern computer games are becoming increasingly complex and only experienced players can fully master the game controls. Accordingly, many commercial games now provide aids to simplify the player interaction. These aids are based on simple heuristics rules and cannot adapt neither to the current game situation nor to the player game style. In this paper, we suggest that supervised methods can be applied effectively to improve the quality of such game aids. In particular, we focus on the problem of developing an automatic weapon selection aid for Unreal Tournament III, a recent and very popular first person shooter (FPS). We propose a framework to (i) collect a dataset from game sessions, (ii) learn a policy to automatically select the weapon, and (iii) deploy the learned models in the game to replace the default weapon-switching aid provided in the game distribution. Our approach allows the development of weapon-switching policies that are aware of the current game context and can also imitate a particular game style.