Imperfect Information Flow: Modelling Channels and Defaultsin Domain Theory

不完美信息流：领域理论中的渠道和默认建模

• 批准号: 9509067
• 负责人: William Rounds
• 金额: $ 22.4万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-01-01 至 1999-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9509067&HistoricalAwards=false
• 关键词: Imperfect; Information; Flow; Modelling; Channels

IRI-9509067 William C. Rounds University of Michigan $84,231 - 12 mos. Imperfect Information Flow: Modeling Channels and Defaults in Domain Theory This work is an attempt to use techniques used in the semantics of programming languages to unify some concepts in intelligent systems modeling. More specifically, it studies the flow of information which admits errors but still allows useful information to be transmitted. In previous work, a theory of such information flow, called default model theory , grounded in domain theory, has been developed. Default model theory allows information used at one point in a computation to be overwritten when new "strict" information becomes available, providing a means of understanding default and nonmonotonic reasoning from the perspective of information channels. This work will also investigate applications to natural language processing, logic programming, and database handling.

IRI-9509067威廉·C·罗兹密歇根大学84,231-12莫尔斯不完全信息流：领域理论中的建模渠道和缺陷这项工作是一种尝试，它使用程序设计语言语义中的技术来统一智能系统建模中的一些概念。更具体地说，它研究承认错误但仍允许传输有用信息的信息流。在以前的工作中，已经发展了一种基于领域理论的这种信息流的理论，称为缺省模型理论。缺省模型理论允许当新的“严格”信息可用时，在计算中的某一点上使用的信息被覆盖，这提供了一种从信息渠道的角度理解缺省和非单调推理的方法。这项工作还将调查在自然语言处理、逻辑编程和数据库处理方面的应用。