OPPONENT-BASED TACTIC SELECTION FOR A FIRST PERSON SHOOTER GAME

David Thomson

2011

Abstract

Video games are quickly becoming a significant part of society with a growing industry that employs a wide range of talent, from programmers to graphic artists. Video games are also becoming an interesting and useful testbed for Artificial Intelligence research. Complex, realistic environmental constraints, as well as performance considerations demand highly efficient AI techniques. At the same time, the AI component of a video game may define the ongoing commercial success, or failure, of a particular game or game engine. This research details an approach to opponent modeling in a first person shooter game, and evaluates proficiency gains facilitated by such a technique. Information about the user is recorded and used by the existing Artificial Intelligence component to select tactics for any given opponent. The evaluation results show that when computer characters use such modeling they are more effective than when they do not model their opponent.

References

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Paper Citation


in Harvard Style

Thomson D. (2011). OPPONENT-BASED TACTIC SELECTION FOR A FIRST PERSON SHOOTER GAME . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 591-594. DOI: 10.5220/0003178905910594


in Bibtex Style

@conference{icaart11,
author={David Thomson},
title={OPPONENT-BASED TACTIC SELECTION FOR A FIRST PERSON SHOOTER GAME },
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={591-594},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003178905910594},
isbn={978-989-8425-40-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - OPPONENT-BASED TACTIC SELECTION FOR A FIRST PERSON SHOOTER GAME
SN - 978-989-8425-40-9
AU - Thomson D.
PY - 2011
SP - 591
EP - 594
DO - 10.5220/0003178905910594