Collaborative Research: Major: Co-evolution of Designers and Critics for Fast Exploratory Form-finding

合作研究：专业：设计师和评论家的快速探索性找形的共同进化

• 批准号: 0757478
• 负责人: Hod Lipson
• 金额: $ 26.5万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0757478&HistoricalAwards=false
• 关键词: Collaborative; Research; Major; Co; evolution

This project expands the capability of man-and-machine design through a creativity enhancing tool which amplifies the human design process by a novel fusion of interactive design with generative coevolution. The project involves the development of a Web-based, Interactive Evolutionary Algorithm to enhance the creativity of human users in designing complex three-dimensional forms, such as tensegrity architecture. A Co-Evolutionary User Modeling Algorithm capable of generating and maintaining a population of user models will serve as critic and collaborator for the human user. By learning the user's implicit goals and cognitive style we can accelerate the creative design process. A creativity-enhancing generative representation capable of encoding families of designs will capture underlying design dimensions. The design engine will be responsible for integrating the information from the evolved user models in order to automatically generate both surprising (critical) and predictable (collaborative) candidate designs for the human designer. The project develops measures of the creativity of the human-computer design system as a whole, by measuring the complexity and novelty of designs produced by the human user. The ability to enhance a user's creativity, and the ability to rapidly synthesize the demands of a large set of users, has immediate applications in several design domains outside of engineering and architecture. The enhancement of educational software, the design of consumer packaging, and artistic endeavors, among many others, all have much to gain from an open ended framework capable of collaborative discovery.

该项目通过一个创造力增强工具来扩展人机设计的能力，该工具通过交互式设计与生成式协同进化的新颖融合来放大人类设计过程。该项目涉及开发一种基于Web的交互式进化算法，以提高人类用户在设计复杂三维形式（如张拉整体建筑）时的创造力。能够生成和维护用户模型的群体的协同进化用户建模算法将作为人类用户的批评者和合作者。通过学习用户的隐性目标和认知风格，我们可以加速创新设计过程。一个创造力增强的生成表示能够编码设计的家庭将捕获潜在的设计尺寸。设计引擎将负责整合来自演化用户模型的信息，以便为人类设计师自动生成令人惊讶的（关键的）和可预测的（协作的）候选设计。该项目通过测量人类用户产生的设计的复杂性和新奇，开发了人机设计系统作为一个整体的创造力的衡量标准。增强用户创造力的能力，以及快速综合大量用户需求的能力，在工程和建筑之外的几个设计领域中具有直接的应用。教育软件的增强，消费包装的设计和艺术创作，以及许多其他方面，都可以从一个能够协作发现的开放式框架中获益匪浅。