Interactive Evolution of Particle Systems for Computer Graphics and Animation

    Authors

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

    Comments

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    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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