INSPIRE Track 1: Is Evolvability Driven By Emergent Modularity? Biomimetic robots, gene inspired information structures, and the evolvability of intelligent agents

INSPIRE 轨道 1：可进化性是由新兴模块化驱动的吗？

• 批准号: 1344227
• 负责人: Kenneth Livingston
• 金额: $ 99.93万
• 依托单位: Vassar College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1344227&HistoricalAwards=false
• 关键词: INSPIRE; Track; Evolvability; Driven; Emergent

This INSPIRE award is partially funded by the Evolutionary Processes program in the Division of Environmental Biology in the Directorate for Biological Sciences, the Behavioral Systems program in the Division of Integrative Organismal Systems in the Directorate for Biological Sciences, and the Information Integration and Informatics program in the Division of Information & Intelligent Systems in the Directorate for Computer & Information Science & Engineering.For millennia, humans have bred organisms to produce better food, clothes, and companionship. Recently, scientists have learned how to breed robots, evolving simulated creatures in virtual worlds, or physical robots in the real world. By combining the evolutionary process with robotic engineering, more complex and novel designs should be possible compared to traditional methods. In spite of the promise, so far evolved robots only do simple things like walk, navigate, or pick up objects. What limits progress is a lack of understanding of "evolvability," the capacity of organisms (or robots) to change and become more complex. Understanding evolvability is the main goal of this project: researchers will borrow ideas from modern genetics so their robots mutate and develop in ways that are similar to how biological creatures do. In theory, this could produce simple robots that evolve into ever more complex, capable and useful robots.Understanding how complexity evolves is central to the study of life, and may enable even non-specialists to automatically and continuously produce diverse kinds of machines. By linking complexity, genetics, and evolution, this project seeks to discover new principles that can be applied in science and industry. To help convert scientific principles into innovation drivers, online software will be created to show how to evolve virtual or physical robots; this will help students learn about engineering, biology, and how to apply both to technology. Finally, evolutionary robotics can be used to solve complex problems in robotic control that defy logical programming solutions, so this research can help companies that manufacture robots.

INSPIRE奖的部分资金来自于生物科学局环境生物学部的进化过程项目、生物科学局综合有机体系统学部的行为系统项目，以及计算机与信息科学与工程局信息与智能系统学部的信息集成与信息学项目。几千年来，人类一直在培育生物，以生产更好的食物、衣服和伴侣。最近，科学家们已经学会了如何培育机器人，在虚拟世界中进化模拟生物，或在现实世界中进化物理机器人。通过将进化过程与机器人工程相结合，可以实现比传统方法更复杂、更新颖的设计。尽管前景光明，但迄今为止，进化的机器人只能做一些简单的事情，比如走路、导航或捡东西。限制进步的是缺乏对“可进化性”的理解，即生物体（或机器人）变化和变得更复杂的能力。了解可进化性是这个项目的主要目标：研究人员将借鉴现代遗传学的思想，使他们的机器人以与生物相似的方式突变和发展。从理论上讲，这可以使简单的机器人进化成更复杂、更有能力、更有用的机器人。了解复杂性是如何进化的是研究生命的核心，它甚至可以使非专业人士自动地、连续地制造出各种各样的机器。通过将复杂性、遗传学和进化联系起来，该项目寻求发现可以应用于科学和工业的新原理。为了帮助将科学原理转化为创新驱动力，将创建在线软件来展示如何进化虚拟或物理机器人；这将帮助学生学习工程学、生物学，以及如何将两者应用于技术。最后，进化机器人技术可以用来解决机器人控制中违背逻辑编程解决方案的复杂问题，因此这项研究可以帮助制造机器人的公司。