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
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.