INSPIRE: Signals to Symbols: From Bio-inspired Hardware to Cognitive Systems

该INSPIRE奖部分由社会、行为和经济科学理事会行为、认知和社会科学部的学习中心科学项目资助；社会、行为和经济科学理事会行为、认知和社会科学部的感知、行动和认知项目；工程局电气通信和网络系统部门的能源、电力和自适应系统项目；以及数学和物理科学理事会数学科学部的应用数学和数学生物学项目。该研究项目借鉴了许多学科（神经科学、认知科学、计算科学、数学和工程）的知识，以创建能够解释观察到的、复杂的人类运动和行为的认知系统。将开发新的设计方法，以整合感官模式（视觉、听觉、触觉）及其对高级认知功能（语言、推理）的支持。现有的方法往往是模块化组件的组合，每个组件都独立解决其任务，与之相反，该团队采用了一种名为“主动认知”的新方法，具有以下特点：1)不同的感知过程（视觉、听觉和触觉）、认知和运动控制不是孤立地建模，而是按照动力系统理论的传统，将各个模块整合起来，共同开发能力，以获得一个“整体大于部分之和”的推理系统；2)信号的低层次处理与高层次符号信息的处理不再分离，它们将在一个持续的对话中相互作用，这样高层次的知识就会利用感知；3)不再将物理体现从算法考虑中分离出来，将开发受生物学启发的实时硬件，通过集成信号和符号来实现复杂的功能。该项目分为两个工作组。第一个小组将开发一种认知机器人，它可以利用受生物启发的硬件捕获的视觉和听觉信号来识别复杂的人类活动。第二组将通过脑电图和脑磁图测量人类对听觉和视觉的反应来研究人类的注意力，随后将研究结果应用于机器人。每年为期三周的实践研讨会将教育学生，作为团队想法的试验场，并激发新的合作。本次研讨会还将吸引跨学科研究团体的参与，这些研究团体围绕建立生物学启发的认知系统的目标而形成。成功整合认知系统的不同组成部分（硬件、传感器和软件）有可能催生一个受生物启发的认知系统新产业，包括家用和服务机器人，以及智能交通和智能制造系统。此外，这个跨学科的项目将在一个新的工程重点领域的能力建设和认知系统工程师的培训中发挥重要作用，这些工程师需要计算机科学、电子工程和认知神经科学的综合专业知识。

This INSPIRE award is partially funded by the Science of Learning Centers Program in the Division of Behavioral, Cognitive and Social Sciences in the Directorate for Social, Behavioral and Economic Sciences; the Perception, Action, and Cognition Program in the Division of Behavioral, Cognitive and Social Sciences in the Directorate for Social, Behavioral and Economic Sciences; the Energy, Power, and Adaptive Systems Program in the Division of Electrical Communication and Cyber Systems in the Directorate of Engineering; and the Applied Mathematics and Mathematical Biology Program in the Division of Mathematical Sciences in the Directorate for Mathematical and Physical Sciences. This research project draws on knowledge from many disciplines (neuroscience, cognitive science, computational science, mathematics and engineering) to create cognitive systems capable of interpreting observed, complex human movements and actions. New design methodologies will be developed for the integration of sensory modalities (vision, audition, touch) and their support of higher cognitive function (language, reasoning). In contrast to existing approaches which tend to be assemblies of modular components each solving its task in isolation, this team takes a novel approach called Active Cognition which has the following features: 1) Instead of modeling the different perceptual processes (vision, audition, and haptics), cognition, and motor control in isolation, the modules are integrated and capabilities co-developed in the tradition of dynamical systems theory to obtain a reasoning system where "the whole is greater than the sum of its parts"; 2) instead of segregating the low level processing of signals from the processing of higher level symbolic information, they will interact in a continuous dialogue, such that high level knowledge will leverage perception; and 3) instead of separating physical embodiment from algorithmic considerations, biologically inspired real-time hardware will be developed that implements complex functions by integrating signals and symbols. The project is organized in two working groups. The first group will develop a cognitive robot that can recognize complex human activities using visual and auditory signals captured by biological-inspired hardware. The second group will study attention in humans by measuring human response to audition and vision through EEG and MEG, and subsequently implementing the findings in robots. A yearly three-week, hands-on workshop will educate students, serve as testing ground for the team's ideas, and stimulate new collaborations. This workshop will also engage the involvement of the interdisciplinary research community that has formed around the goal of building biologically inspired cognitive systems. Success in integrating different components of a cognitive system (hardware, sensors, and software) has the potential to catalyze a new industry of biologically-inspired cognitive systems, including household and service robots, and systems for intelligent transportation and smart manufacturing. In addition, this interdisciplinary project will play a significant role in building capacity for a new emphasis area in engineering and training of cognitive systems engineers who need combined expertise in computer science, electrical engineering and cognitive neuroscience.