INSPIRE Track 1: Gradient Symbolic Computation

INSPIRE奖的部分资金来自社会、行为和经济科学局行为和认知科学部的语言学计划和感知、行动和认知计划；计算机和信息科学与工程局的信息和智能系统部的稳健智能计划；以及计算机和信息科学与工程局的计算机和网络系统部的算法基础计划。具体而言，结构化符号的组合系统在语言、运动控制、复杂动作规划、学习和高级视觉等领域渗透人类认知。尽管如此，大脑使用的计算设备是基于连续的、基于激活的信息传播，通过复杂的神经元网络。认知科学的一个基本问题是如何将梯度的、连续的神经计算与认知的离散组合维度相结合。这个谜题的解决方案将提供对大脑的更深层次的理解，也可能成为新一代计算系统的基础，能够真正地产生类似大脑的行为。在斯摩棱斯基博士的指导下，研究小组将通过探索和测试他们的梯度符号计算(GSC)理论在语言领域的预测来开发一种方法来解决这个谜题。他们的努力将包括发展GSC的正式的数学基础。同时，个人信息系统将开发一个建模梯度符号处理的框架。为此，PI将使用计算机建模和实验心理语言学研究现象，这些现象代表了语言和语言处理的形态-语音、句法和语义特征。这项工作的更广泛影响包括有可能将通用计算转变为未来的计算机设计方法，在计算机语言处理方面提供创新，并使我们在理解人类语言、疾病中的损害以及学习和补救方面取得重大进展。该项目还大力参与STEM教育。本科生、研究生和博士后研究人员都将在整合实验、理论和计算方法的高度跨学科的STEM研究中发挥关键作用。创建的新型计算将为开发连接计算理论、心理学和语言学的课程提供一个综合框架。在这些课程中开发的教学材料将被公开提供，以促进其他机构的本科生和研究生课程的发展。

This INSPIRE award is partially funded by the Linguistics Program and the Perception, Action & Cognition Program in the Division of Behavioral and Cognitive Sciences in the Directorate for Social, Behavioral & Economic Sciences; by the Robust Intelligence Program in the Division of Information & Intelligent Systems in the Directorate for Computer & Information Science & Engineering; and by the Algorithmic Foundations Program in the Division of Computer and Network Systems in the Directorate for Computer & Information Science & Engineering.Discrete, combinatorial systems of structured symbols permeate human cognition in domains such as language, motor control, complex action planning, learning, and higher-level vision. Nonetheless, the computational apparatus that the brain exploits is based on continuous, activation-based propagation of information through complex networks of neurons. A fundamental problem of the cognitive sciences is how to integrate gradient, continuous neural computation with the discrete combinatorial dimension of cognition. The solution to this puzzle will provide a deeper understanding of the mind and may also serve as the basis of a new generation of computing systems capable of authentically brain-like behavior.Under the direction of Dr. Smolensky, the research team will develop an approach to this puzzle by exploring and testing the predictions of their theory of Gradient Symbolic Computation (GSC) in the domain of language. Their efforts will include the development of the formal, mathematical foundations of GSC. In parallel, the PIs will develop a framework for modeling Gradient Symbolic Processing. To that end, the PIs will use computational modeling and experimental psycholinguistic studies of phenomena that typify the morpho-phonological, syntactic, and semantic characteristics of language and language processing. The broader impacts of the work include the potential to transform general computing for future approaches to computer design, to provide innovations in computer language processing, and to empower major advances in our understanding of human language, its impairment in disease, and its learning and remediation. The project also strongly engages STEM education. Undergraduate, graduate, and post-doctoral researchers will all play key roles in highly interdisciplinary STEM research integrating experimental, theoretical, and computational methods. The new type of computation created will provide an integrative framework for developing courses bridging computation theory, psychology, and linguistics. Pedagogical materials developed in these courses will be made publicly available to facilitate undergraduate and graduate program development at other institutions.