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Permanent link (DOI): https://doi.org/10.7939/R3F99D

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Predicting opponent locations in first-person shooter video games Open Access

Descriptions

Other title
Subject/Keyword
opponent modelling
particle filter
hidden semi-Markov model
believability
video games
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Hladky, Stephen Michael
Supervisor and department
Bulitko, Vadim (Computing Science)
Examining committee member and department
Spetch, Marcia (Psychology)
Bowling, Michael (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2009-09-04T21:33:59Z
Graduation date
2009-11
Degree
Master of Science
Degree level
Master's
Abstract
Commercial video game developers constantly strive to create intelligent humanoid characters that are controlled by computers. To ensure computer opponents are challenging to human players, these characters are often allowed to cheat. Although they appear skillful at playing video games, cheating characters may not behave in a human-like manner and can contribute to a lack of player enjoyment if caught. This work investigates the problem of predicting opponent positions in the video game Counter-Strike: Source without cheating. Prediction models are machine-learned from records of past matches and are informed only by game information available to a human player. Results show that the best models estimate opponent positions with similar or better accuracy than human experts. Moreover, the mistakes these models make are closer to human predictions than actual opponent locations perturbed by a corresponding amount of Gaussian noise.
Language
English
DOI
doi:10.7939/R3F99D
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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