Title

Interactive Evolution of Particle Systems for Computer Graphics and Animation

Authors

Authors

E. J. Hastings; R. K. Guha;K. O. Stanley

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

IEEE Trans. Evol. Comput.

Keywords

Interactive evolutionary computation (IEC); neuroevolution of augmenting; topologies (NEAT); particle systems; NEURAL-NETWORKS; TOPOLOGIES; CLOTH; MODEL; Computer Science, Artificial Intelligence; Computer Science, Theory &; Methods

Abstract

Interactive Evolutionary Computation (IEC) creates the intriguing possibility that a large variety of useful content can be produced quickly and easily for practical computer graphics and gaming applications. To show that IEC can produce such content, this paper applies IEC to particle system effects, which are the de facto method in computer graphics for generating fire, smoke, explosions, electricity, water, and many other special effects. While particle systems are capable of producing a broad array of effects, they require substantial mathematical and programming knowledge to produce. Therefore, efficient particle system generation tools are required for content developers to produce special effects in a timely manner. This paper details the design, representation, and animation of particle systems via two IEC tools called NEAT Particles and NEAT Projectiles. Both tools evolve artificial neural networks (ANN) with the NeuroEvolution of Augmenting Topologies (NEAT) method to control the behavior of particles. NEAT Particles evolves general-purpose particle effects, whereas NEAT Projectiles specializes in evolving particle weapon effects for video games. The primary advantage of this NEAT-based IEC approach is to decouple the creation of new effects from mathematics and programming, enabling content developers without programming knowledge to produce complex effects. Furthermore, it allows content designers to produce a broader range of effects than typical development tools. Finally, it acts as a concept generator, allowing content creators to interactively and efficiently explore the space of possible effects. Both NEAT Particles and NEAT Projectiles demonstrate how IEC can evolve useful content for graphical media and games, and are together a step toward the larger goal of automated content generation.

Journal Title

Ieee Transactions on Evolutionary Computation

Volume

13

Issue/Number

2

Publication Date

1-1-2009

Document Type

Article

Language

English

First Page

418

Last Page

432

WOS Identifier

WOS:000265091900013

ISSN

1089-778X

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