CAREER: Creating Robust, Adaptable Computational Intelligence by Recreating Key Properties of Animal Brains

自然动物表现出令人敬畏的适应性和健壮性（例如三条腿的狗仍然可以奔跑和抓住飞盘）。神经科学家认为动物如此有能力的一个原因是，它们的大脑在结构上有组织，它们表现出神经的规律性、模块化和层次性。该项目将测试这些神经特性是否也能提高进化的计算代理（特别是机器人）的鲁棒性、适应性和整体智能。进化算法（EAs）是通过进化而不是设计计算代理来产生自然界中常见的品质，比如鲁棒性和适应性。虽然人工智能的表现往往超过人类工程师，但它们设计的机器人身体和大脑与自然动物相比相形见绌。PI （Clune教授）和其他人的最新进展使神经网络（计算大脑）的进化表现出规律性、模块化和层次性。Clune教授和他的学生将测试规则性、模块化和层次性是否单独或结合起来提高(1)对噪声的稳健性(2)对损害的稳健性(3)对新环境的适应性(4)学习能力，以及(5)整体智力（以解决不同复杂性挑战的能力来衡量）。基于他之前的工作和初步结果，Clune预计神经的规律性、模块化和层次性可以增加所有这些理想的行为品质。这些知识将加速人类部署有效的自主机器人的能力，这将为社会带来巨大的利益（例如搜索和救援，灭火和老年人护理）。这项研究与一个紧密结合的教育计划相结合，通过拉勒米的机器人俱乐部、进化机器人的研究型课程、通过视频和媒体进行的公共教育，以及扩大研究生培训的参与，产生更广泛的影响。

Natural animals display awe-inspiring adaptability and robustness (e.g. three-legged dogs that can still run and catch frisbees). One reason neuroscientists believe animals are so capable is because their brains are structurally organized in that they exhibit neural regularity, modularity, and hierarchy. This project will test whether those neural properties also improve the robustness, adaptability, and overall intelligence of evolved computational agents, specifically robots. Evolutionary algorithms (EAs) evolve, rather than engineer, computational agents to produce qualities seen in nature, such as robustness and adaptability. While EAs often outperform human engineers, the robot bodies and brains they design pale in comparison to those of natural animals. Recent advances by the PI (Professor Clune) and others enable the evolution of neural networks (computational brains) that exhibit regularity, modularity, and hierarchy.Professor Clune and his students will test whether regularity, modularity, and hierarchy, separately and in combination, improve (1) robustness to noise (2) robustness to damage (3) adaptability to new environments (4) learning, and (5) overall intelligence, measured as the ability to solve challenges of varying complexities. Based on his previous work and preliminary results, Clune anticipates that neural regularity, modularity, and hierarchy could increase all of these desirable behavioral qualities. Such knowledge will accelerate humanity's ability to deploy effective, autonomous robots, which will provide tremendous benefits to society (e.g. search and rescue, putting out fires, and elderly care). The research is woven into a tightly integrated educational plan that generates broader impacts via a robotics club in Laramie, a research-oriented course in evolutionary robotics, public education via videos and the press, and broadening participation in graduate training.