Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making

Abstract. Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for computer-supported collaborative work. Moreover, such a user-centered approach fuses human and computer partners in a natural way. This paper presents a first test, as well as analyzes the obtained results, of real human and computer collaboration powered by the fusion of human-based genetics algorithms and chance discovery. 1 Motivation DISCUS (Distributed Innovation and Scalable Collaboration in Uncertain Settings) [1] is an endeavor to create innovation support mechanisms. Such innovation support mechanisms rely on the metaphor of genetic algorithms as models of human innovation. The metaphor establishes both a qualitative and quantitative pathway for the design of such systems, taking advantage of mechanism and analytical design theory developed for more than twenty years on competent GAs [2]. Human-base...

• Type: Conference
• Year: 2004
• Where: GECCO
• Authors: Xavier Llorà, Kei Ohnishi, Ying-Ping Chen, David E. Goldberg, Michael Welge
• Keywords: Chance Discovery, GECCO 2004, Human-based Genetic Algorithms, Innovation Support