Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Computing, Health and Science

School

Computer and Information Science

RAS ID

5413

Comments

This article was originally published as: Soni, B. A., & Hingston, P. F. (2008). Bots Trained to Play Like a Human are More Fun. Proceedings of International Joint Conference on Neural Networks. (pp. 363-369). Hong Kong. IEEE. Original article available here

Abstract

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.

 
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Link to publisher version (DOI)

10.1109/IJCNN.2008.4633818