Population evolution analysis in collective intelligence design ecosystem |
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| Affiliation: | 1. Department of Mechanical Engineering, Tianjin University, Tianjin 300350, China;2. Department of Mechanical Engineering, Tianjin Ren’ai College, Tianjin 301636, China;3. Institute of Advance Design and Manufacturing, Southwest Jiaotong University, Chengdu 610031, China;1. Instituto Universitario de Investigación en Tecnología Centrada en el Ser Humano, Universitat Politècnica de València, Valencia, Spain;2. Dpto. de Ingeniería Mecánica y Construcción, Universitat Jaume I, Castellón, Spain;3. School of Engineering Technology, Purdue University, West Lafayette, IN, USA;1. Institute of Artificial Intelligence & Robotics (IAIR), Key Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic and Transportation Engineering, Central South University, Changsha 410075, Hunan, China;2. School of Civil Engineering, University of Leeds, LS2 9JT Leeds, UK;1. College of Mechanical Engineering, Tongji University, Shanghai 201804, China;2. Shanghai Metro Shield Machine Equipment & Engineering Co., Ltd, Shanghai 201804, China |
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| Abstract: | The Collective Intelligent Design Ecosystem is a dynamic ecosystem founded on an online design platform that leverages collective intelligence to support the creation of novel products. The system's primary components are its users and designers. Maintaining the system's sustainability requires expanding the scale of the designer and user populations as it evolves to stabilize. However, the unity of ecological interactions between various populations is fragmented in contemporary studies of population-scale evolution, and the parameterization of evolutionary models is illogical. To overcome this gap, this research provides a population evolution model of collective intelligent design incorporating participants' intra- and interspecific ecological connections. The model's validity is verified by the evolutionary simulation of 110 designers and 5990 users of China's largest collective intelligence design platform, the Zhubajie platform, and illuminating conclusions are in turn drawn from this simulation. First, the designer's influence on the user is greater than the user's impact on the designer. Second, keeping current members engaged is more crucial to the system's viability than luring in new ones. Third, fostering collaboration among designers while retaining user competitiveness can promote system growth. Fourth, decreasing the reliance between particular designers and users might hasten the system's evolution. |
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| Keywords: | System sustainability Collective Intelligence Design Ecosystem Population Evolution Online product design platform Lotka-Volterra |
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