Faculty of Computing, Health and Science
School of Computer and Information Science
Computational intelligence methods are well-suited for use in computer controlled opponents for video games. In many other applications of these methods, the aim is to simulate near-optimal intelligent behaviour. But in video games, the aim is to provide interesting opponents for human players, not optimal ones. In this study, we trained neural network-based computer controlled opponents to play like a human in a popular first-person shooter. We then had gamers play-test these opponents as well as a hand-coded opponent, and surveyed them to find out which opponents they enjoyed more. Our results show that the neural network-based opponents were clearly preferred.