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Researches on Emergent Design by means of Interactive Evolutionary Computation and Genetic Programming

交互式进化计算和遗传编程的应急设计研究

基本信息

批准号：
15300040
负责人：
IBA Hitoshi
金额：
$ 5.44万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

项目摘要

In this research, we have used Genetic Programming (GP) to establish the effective emergent design system by means of Interactive Evolutionary Computation (IEC).Conventional optimization methods optimize target systems based on evaluation or cost functions and have been used for most of system optimization and parameter tuning. According to the increase of the importance of human factors, however, the cases that the performance of system design must be evaluated based on human subjective evaluations and domain knowledge came to increase. These cases include artistic systems generating preferable computer graphics (CG) or music, hearing-aid fitting for maximizing hearing satisfaction of its users, robots whose behaviors let our human feel comfortable, and others. IEC is a technique that optimizes target systems based on human evaluation. The number of IEC research has increased since 1990's, and it is widely used in artistic field, engineering field, and education and other fields nowadays. Not only IEC application research but also IEC interface research to reduce IEC users' fatigue problem increases, too.To solve the above difficulties, in this research, we have realized GP-based emergent design framework. The effectiveness of our approach has been demonstrated by several applications, e.g., analog circuit design, musical composition, evolutionary robotics, agent designs in WWW space, and multi-agent cooperation learning.

在本研究中，我们利用遗传规划（GP），通过交互进化计算（IEC）建立有效的紧急设计系统。传统的优化方法是基于评价函数或成本函数对目标系统进行优化，并已用于大多数系统优化和参数整定。然而，随着人的因素重要性的提高，必须基于人的主观评价和领域知识来评价系统设计性能的情况有所增加。这些例子包括产生更好的计算机图形（CG）或音乐的艺术系统，最大限度地提高用户听力满意度的助听器，行为让我们人类感到舒适的机器人等等。IEC是一种基于人的评价来优化目标系统的技术。自20世纪90年代以来，IEC的研究数量不断增加，如今已广泛应用于艺术领域、工程领域和教育等领域。为了减少IEC用户的疲劳问题，IEC的应用研究和接口研究也越来越多。为了解决上述困难，本研究实现了基于gp的紧急设计框架。我们的方法的有效性已经通过几个应用得到了证明，例如模拟电路设计、音乐作曲、进化机器人、WWW空间中的智能体设计和多智能体合作学习。