INSPIRE Track 1: Gradient Symbolic Computation

INSPIRE奖部分由社会、行为与经济科学理事会行为与认知科学部的语言学项目和感知、行动与认知项目资助。由计算机与信息科学与工程理事会信息与智能系统部门的稳健情报项目；以及计算机与信息科学与工程理事会计算机与网络系统部门的算法基础项目。结构化符号的离散组合系统渗透到人类认知领域，如语言、运动控制、复杂行动计划、学习和高级视觉。尽管如此，大脑利用的计算装置是基于通过复杂的神经元网络进行连续的、基于激活的信息传播。认知科学的一个基本问题是如何将梯度、连续的神经计算与认知的离散组合维相结合。这个谜题的答案将提供对思维的更深层次的理解，也可能作为新一代计算系统的基础，这些系统能够真正实现类似大脑的行为。在Smolensky博士的指导下，研究小组将通过探索和测试他们在语言领域的梯度符号计算（GSC）理论的预测，来开发一种解决这个难题的方法。他们的努力将包括发展GSC的正式数学基础。同时，pi将开发一个梯度符号处理建模框架。为此，pi将使用计算模型和实验心理语言学研究，研究语言和语言处理的形态音韵、句法和语义特征。这项工作的更广泛的影响包括，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，并在我们对人类语言的理解、其在疾病中的损害、及其学习和补救方面取得重大进展。该项目还大力开展STEM教育。本科生、研究生和博士后研究人员都将在高度跨学科的STEM研究中发挥关键作用，这些研究结合了实验、理论和计算方法。这种新型的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的框架。在这些课程中开发的教学材料将公开提供，以促进其他机构的本科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.