Towards an Integrated Connectionist/Symbolic Theory of Higher Cognition (REU Supplement)

走向更高认知的综合联结主义/符号理论（REU 补充）

• 批准号: 9209265
• 负责人: Paul Smolensky
• 金额: $ 11.7万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-08-01 至 1995-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9209265&HistoricalAwards=false
• 关键词: Towards; Integrated; Connectionist; Symbolic; Theory

ABSTRACT This project develops a research program, the Sub-Symbolic Paradigm (SSP), which exploits connectionist computation as a bridge between numerical neural computation and symbolic mental computation, and forges an integration in which the latter is an approximate higher-level description of the former. While much of connectionist research has addressed problems and data from cognitive psychology, SSP has focused on complementary data and problems in higher cognition that are centrally located in linguistics and the foundations of cognitive science. SSP has already made significant progress, including (a) mathematical techniques for representing symbolic structures as lower-level distributed patterns of activity and for (b) performing massively parallel structure-sensitive processing on such representations; (c) the analysis of connectionist computation as maximizing Harmony, a well-formedness measure on representations; (d) contributions to theoretical linguistics in the areas of syntax/semantics and phonology that rely on using Harmony to measure the well-formedness of linguistic structures; and (e) contributions to the foundations of cognitive science deriving from the interpretation of the preceding results. The new research to be supported by the present grant will build on (d), expanding the theory of grammar as a well-formedness optimizing system, and on (e), systematically developing a typology of strategies for connectionist-grounded explanations of the striking productivity of human higher cognition. SSP is contributing to the development of a new methodology for cognitive science which is more than just the sum of those of its sister disciplines, a methodology capable of yielding results which are beyond the reach of all the other disciplines proceeding individually. By integrating linguistic, philosophical, and mathematical analysis, computer simulation, and techniques from both discrete and continuous computation, this new methodology can develop more powerful connectionist systems, innovative symbolic formalisms, and general cognitive principles that constitute real progress towards the unification of connectionist and symbolic theories of brain and mind.

摘要 该项目开发了一个研究项目， 范式（SSP），它利用连接主义计算作为 数字神经计算和符号心理之间的桥梁 计算，并伪造一个集成，其中后者是一个 近似于前者的高级描述。 虽然许多联结主义的研究已经解决了问题， 从认知心理学的数据，SSP专注于补充 数据和问题在更高的认知中， 语言学和认知科学的基础。 SSP有 已经取得了重大进展，包括（a）数学 用于将符号结构表示为较低级别的技术 活动的分布式模式，以及用于（B）执行 大规模并行结构敏感处理， （c）联结主义计算的分析 作为最大化和谐，一个良好的形式的措施， （d）对理论语言学的贡献 依赖于使用的句法/语义和音韵学领域 和谐度是衡量语言结构是否合理的标准; 以及（e）对认知科学基础的贡献 从前面的结果的解释得出。 这项新的研究将由目前的赠款支持， （d）将语法理论扩展为一种形式良好的理论， 优化系统，以及（e）系统地开发一个 基于联结主义的解释的策略类型学 人类高级认知的惊人生产力。 SSP致力于开发一种新的方法， 认知科学不仅仅是 它的姐妹学科，一种能够产生 其他学科无法企及的成果 单独进行。 通过整合语言， 哲学，数学分析，计算机模拟， 以及离散和连续计算的技术， 这种新的方法可以培养出更强大的联结主义者， 系统，创新的符号形式主义，和一般的认知 构成统一的真实的进展的原则 大脑和心智的联结主义和符号理论。