Emergent effects in massive agent swarms in real-time game environments

Knight, Owen, Wilkin, Tim and Bangay, Shaun 2013, Emergent effects in massive agent swarms in real-time game environments, in IGIC 2013 : Proceedings of the 5th International IEEE Consumer Electronic Society Games Innovation Conference, IEEE, Piscataway, N.J., pp. 114-118.

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Title Emergent effects in massive agent swarms in real-time game environments
Author(s) Knight, Owen
Wilkin, Tim
Bangay, Shaun
Conference name International IEEE Consumer Electronic Society Games Innovation Conference (5th : 2013 : Vancouver, BC, Canada)
Conference location Vancouver, BC, Canada
Conference dates 23-25 Sep. 2013
Title of proceedings IGIC 2013 : Proceedings of the 5th International IEEE Consumer Electronic Society Games Innovation Conference
Editor(s) [Unknown]
Publication date 2013
Conference series International IEEE Consumer Electronic Society Games Innovation Conference
Start page 114
End page 118
Total pages 5
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) emergence
gpu
steering behaviour
swarms
Summary  Computational efficiency and hence the scale of agent-based swarm simulations is bound by the nearest neighbour computation for each agent. This article proposes the use of GPU texture memory to implement lookup tables for a spatial partitioning based k-Nearest Neighbours algorithm. These improvements allow simulation of swarms of 220 agents at higher rates than the current best alternative algorithms. This approach is incorporated into an existing framework for simulating steering behaviours allowing for a complete implementation of massive agent swarm simulations, with per agent behaviour preferences, on a Graphics Processing Unit. These simulations have enabled an investigation of the emergent dynamics that occur when massive swarms interact with a choke point in their environment. Various modes of sustained dynamics with temporal and spatial coherence are identified when a critical mass of agents is simulated and some elementary properties are presented. The algorithms presented in this article enable researchers and content designers in games and movies to implement truly massive agent swarms in real time and thus provide a basis for further identification and analysis of the emergent dynamics in these swarms. This will improve not only the scale of swarms used in commercial games and movies but will also improve the reliability of swarm behaviour with respect to content design goals.
ISBN 9781479912445
ISSN 2166-6741
Language rus
Field of Research 080102 Artificial Life
Socio Economic Objective 890203 Computer Gaming Software
HERDC Research category E1 Full written paper - refereed
HERDC collection year 2013
Copyright notice ©2013, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30058478

Document type: Conference Paper
Collection: School of Information Technology
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Created: Wed, 27 Nov 2013, 07:34:38 EST by Shaun Bangay

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