Collaborative interactive evolution
Sean R. Szumlanski, Annie S. Wu, Charles E. Hughes · 2005
This paper examines the efficacy of genetic algorithms (GAs) in combining input from multiple users to control a single interactive system, such as an educational exhibit at a museum. Specifically, the idea of collaborative interactive evolution (that is, interactive evolution with input from multiple users) is introduced for this purpose. Two fitness functions are proposed to guide the collaborative interactive evolution, as well as two non-GA methods for combining user input. The usefulness and success of each of these methods is examined, and the GA is shown to be a viable means for combining user input for the control of a single interactive system.