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

该INSPIRE奖部分由生物科学理事会环境生物学部门的进化过程计划，生物科学理事会综合有机系统部门的行为系统计划，以及计算机信息科学工程理事会信息智能系统部门的信息集成和信息学计划资助。最近，科学家们已经学会了如何繁殖机器人，在虚拟世界中进化模拟生物，或者在真实的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，与传统方法相比，更复杂和新颖的设计应该是可能的。 尽管有这样的希望，但到目前为止，进化的机器人只会做简单的事情，比如走路、导航或捡起物体。限制进步的是对“进化性”的缺乏理解，即生物体（或机器人）改变并变得更加复杂的能力。 理解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，使他们的机器人以类似于生物的方式变异和发展。从理论上讲，这可以产生简单的机器人，这些机器人可以进化成更复杂、更有能力和更有用的机器人。了解复杂性如何进化是研究生命的核心，甚至可以使非专业人员自动和连续地生产各种机器。 通过将复杂性、遗传学和进化联系起来，该项目旨在发现可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的复杂问题，这些问题违背了逻辑编程的解决方案，因此这项研究可以帮助制造机器人的公司。

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.