Framework for Enabling Scalable Learning Game AI

Gabriel Iuhasz, Victor Ion Munteanu, Viorel Negru

Abstract

The video game industry is a multibillion-dollar industry in which, due to general short deadlines, game visuals as well as gameplay elements are worked in parallel up until the very last minute. This means that even if the AI system has been designed in parallel with the other game elements, once a change has been made in the late stages of the game development, the AI may prove to be inadequate to the given job. Our article covers some of the existing frameworks for game AI and proposes a multi-agent system which serves as a framework for scalable learning game AI through integration of existing machine learning techniques.

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Paper Citation


in Harvard Style

Iuhasz G., Ion Munteanu V. and Negru V. (2013). Framework for Enabling Scalable Learning Game AI . In Proceedings of the 8th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-8565-62-4, pages 189-196. DOI: 10.5220/0004449301890196


in Bibtex Style

@conference{enase13,
author={Gabriel Iuhasz and Victor Ion Munteanu and Viorel Negru},
title={Framework for Enabling Scalable Learning Game AI},
booktitle={Proceedings of the 8th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2013},
pages={189-196},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004449301890196},
isbn={978-989-8565-62-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Framework for Enabling Scalable Learning Game AI
SN - 978-989-8565-62-4
AU - Iuhasz G.
AU - Ion Munteanu V.
AU - Negru V.
PY - 2013
SP - 189
EP - 196
DO - 10.5220/0004449301890196