Interactive Evolutionary Computation in Design Applications for Virtual Worlds

Modern films, games and virtual reality are highly dependent on convincing computer graphics. Models of high complexity are a requirement for the successful delivery of many animated scenes and environments. While workflows such as rendering, compositing and animation have been streamlined to accommodate increasing demands, modelling of complex models is still a laborious and costly task. This research introduces the computational benefits of Interactive Genetic Algorithms to computer graphics modelling while compensating the negative effects of user fatigue, a commonly found issue with Interactive Evolutionary Computation. A multi-agent system is used to integrate Genetic Algorithms with computational agents and human designers. This workflow accelerates the layout and distribution of basic elements to form highly complex models. It captures the designer’s intent through interaction, and encourages playful discovery. A modelling pipeline integrating commercially available tools with Human-based Genetic Algorithms is implemented, and a Renderman Interface Bytestream (RIB) archive output is realized to provide easy adaptability for research and industry applications. Comparisons between Interactive Genetic Algorithms and Human-based Genetic Algorithms applied to procedural modelling of computer graphics cities indicate that an agent-based evolutionary approach outperforms a purely human-centric solution: More iterations are possible in less time, which ultimately leads to better results and a superior user experience. Based on initial testing, a range of suggestions for future investigation are given.