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Interactive Genetic Algorithms for use as Creativity Enhancement Tools

机译:用于创造性增强工具的交互式遗传算法

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It is proposed that creativity can be enhanced through the use of interactive genetic algorithms (IGAs). Divergent and convergent thinking are important processes in creativity that we simulate through two separate IGA populations developed by different means. The convergent process hones in on specific designs, while the divergent process explore design possibilities in a fashion beyond pure mutation techniques typically used to introduce population diversity. This study uses Monte Carlo simulation to explore the effect of merging two populations developed by the divergent and convergent methods. The results suggest that population diversity benefits from these population combinations while not adversely affecting the ability of the user to find a goal design. This IGA has also been developed in Adobe Flash so that it can be deployed on the internet to conduct validation and studies of creativity.
机译:建议通过使用交互式遗传算法(IGA)可以提高创造力。发散和趋同思维是创造力的重要过程,我们通过不同手段开发的两个独立的IGA群体模拟。收敛过程在特定设计上致电,而发散过程以通常用于引入人口多样性的纯突变技术的方式探讨设计的设计可能性。本研究采用蒙特卡罗模拟来探索合并由分歧和收敛方法开发的两个人群的效果。结果表明,人口多样性从这些人口组合中受益,同时不会对用户找到目标设计的能力产生不利影响。该IGA也在Adobe Flash中开发,因此可以在互联网上部署,以进行创造力的验证和研究。

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