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Authors: Juliette Lemaitre 1 ; Domitile Lourdeaux 2 and Caroline Chopinaud 3

Affiliations: 1 Université de Technologie de Compiègne and MASA Group, France ; 2 Université de Technologie de Compiègne, France ; 3 MASA Group, France

ISBN: 978-989-758-073-4

ISSN: 2184-433X

Keyword(s): Strategy, Behavior Modeling, Game Design, Player Experience, Adaptation.

Related Ontology Subjects/Areas/Topics: Agent Models and Architectures ; Agents ; Artificial Intelligence ; Cooperation and Coordination ; Knowledge Representation and Reasoning ; Reactive AI ; Soft Computing ; Symbolic Systems

Abstract: The artificial intelligence used for opponent non-player characters in commercial real-time strategy games is often criticized by players. It is used to discover the game but soon becomes too easy and too predictable. Yet, a lot of research has been done on the subject, and successful complex behaviors have been created, but the systems used are too complicated to be used by the video games industry, as they would need time for the game designer to learn how they function, which ultimately proves prohibitive. Moreover these systems often lack control for the game designer to be adapted to the desired behavior. To address the issue, we propose an accessible strategy model that can adapt itself to the player and can be easily created and modified by the game designer.

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Paper citation in several formats:
Lemaitre, J.; Lourdeaux, D. and Chopinaud, C. (2015). Towards a Resource-based Model of Strategy to Help Designing Opponent AI in RTS Games.In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-073-4, ISSN 2184-433X, pages 210-215. DOI: 10.5220/0005254402100215

@conference{icaart15,
author={Juliette Lemaitre. and Domitile Lourdeaux. and Caroline Chopinaud.},
title={Towards a Resource-based Model of Strategy to Help Designing Opponent AI in RTS Games},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2015},
pages={210-215},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005254402100215},
isbn={978-989-758-073-4},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Towards a Resource-based Model of Strategy to Help Designing Opponent AI in RTS Games
SN - 978-989-758-073-4
AU - Lemaitre, J.
AU - Lourdeaux, D.
AU - Chopinaud, C.
PY - 2015
SP - 210
EP - 215
DO - 10.5220/0005254402100215

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