Collaborative Research on Semantic Unification and its Applications

语义统一及其应用的协作研究

• 批准号: 0098095
• 负责人: Paliath Narendran
• 金额: $ 11.96万
• 依托单位: SUNY at Albany
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-15 至 2005-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0098095&HistoricalAwards=false
• 关键词: Collaborative; Research; Semantic; Unification; its

Proposal #0098095Narendran, PaliathSUNY AlbanySemantic unification has been effectively employed in many subfields of logic, computer science, artificial intelligence and cognitive science, with its most popular use being in resolution, logic programming languages such as Prolog, and the type inference mechanism in the programming language ML. Semantic unification (associative-commutative unification) played a pivotal role in settling open questions in mathematics (e.g. Robbins' conjecture about boolean algebra in 1996 by McCune using the theorem prover EQP). Recently, semantic unification has been found useful also in cryptographic analysis, knowledge representation and distributed computing.This project will be a continuation of research on the theory of semantic unification as well as the design, development and implementation of semantic unification algorithms. This research will be motivated by new applications of semantic unification in cryptographic protocol analysis in conjunction with Catherine Meadows' work on the NRL (Naval Research Laboratory) Protocol Analyzer, in knowledge representation and description logics, induction theorem proving, and process algebra.The new unification algorithms will be first developed and experimented using the Unification Workbench, a tool under development at SUNY, Albany, with the eventual goal of integrating them into application software, the NRL Protocol Analyzer and a rewrite-based induction theorem prover RRL (Rewrite Rule Laboratory) for use in the applications discussed above.This award is one of three in a collaborative research team. The three awards are CCR-0098114 (Deepak Kapur, U New Mexico), CCR-0098270 (Christopher Lynch, Clarkson U), and CCR-0098095 (Paliath Narendran, SUNY Albany).

语义统一已被有效地应用于逻辑、计算机科学、人工智能和认知科学的许多子领域，其最广泛的使用是在归结、逻辑编程语言(如Prolog)和编程语言ML中的类型推理机制中。语义统一(联想-交换统一)在解决数学中未解决的问题中发挥了关键作用(例如，1996年McCune使用定理证明器EQP提出了关于布尔代数的Robbins猜想)。近年来，语义统一在密码分析、知识表示和分布式计算等领域也得到了广泛的应用，本课题将是语义统一理论研究的继续，也是语义统一算法设计、开发和实现的继续。这项研究将受到语义统一在密码协议分析中的新应用的推动，并与Catherine Meadow在NRL(海军研究实验室)协议分析器、知识表示和描述逻辑、归纳定理证明和过程代数方面的工作相结合。新的统一算法将首先使用位于奥尔巴尼的纽约州立大学开发的工具统一工作台进行开发和实验，最终目标是将它们集成到应用软件、NRL协议分析器和基于重写的定理归纳实验室RRL(重写规则实验室)中用于上述应用。该奖项是合作研究团队的三个合作研究团队中的一个。这三个奖项分别是CCR-0098114(新墨西哥州迪帕克卡普尔大学)、CCR-0098270(克里斯托弗·林奇，克拉克森大学)和CCR-0098095(帕利亚斯·纳伦德兰，纽约州立大学奥尔巴尼分校)。