Constraints, Logic Programming and Rule-Based Systems

约束、逻辑编程和基于规则的系统

• 批准号: 8902511
• 负责人: Ken McAloon
• 金额: $ 18.62万
• 依托单位: CUNY Brooklyn College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-10-01 至 1992-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8902511&HistoricalAwards=false
• 关键词: Constraints; Logic; Programming; Rule; Based

The Constraint Logic Programming (CLP) scheme of languages provides a framework for reasoning with symbolic and numerical constraints and for linking these methods of computation. It also provides a method for tailoring constraint logic programming languages for specific applications. The research plan includes: (1) to implement sequential and parallel versions of a canonical for algorithm developed by Lassez and McAloon for solving and maintaining systems of constraints and rules, (2) to work on constraint solving techniques for use in implementations of CLP(R) and other constraint logic programming languages, (3) to embed this work in the inference and constraint solving engines of a CLP language called 2LP specifically intended for application to constraint based reasoning and to mixed integer linear optimization problems, (4) to work on a sequent calculus approach to reasoning with constraints, on canonical forms in a general setting and on computational complexity issues. This research can lead to new intelligent systems for dealing with applications classically handled by mixed integer linear programming in the areas of financial applications or resource management and to development of user friendly general purpose applications software for constraints and optimization.

约束逻辑程序设计（CLP）语言 提供了一个用符号和数字进行推理的框架， 约束和连接这些计算方法。 它 还提供了一种裁剪约束逻辑编程的方法， 针对特定应用的语言。 研究计划包括： (1)实现规范的顺序和并行版本， 用于Lassez和McAyer开发的用于求解和 保持约束和规则系统，（2）工作 用于在实施例中使用的约束求解技术 CLP（R）和其他约束逻辑编程语言，（3）到 将这项工作嵌入到推理和约束求解引擎中 一种名为2LP的CLP语言， 应用于基于约束的推理和混合整数 线性最优化问题，（4）研究微积分 方法推理与约束，规范形式在一个 一般设置和计算复杂性问题。 这 研究可以导致新的智能系统来处理 混合整数线性函数处理的经典应用 财务应用程序或资源领域的编程 管理和开发用户友好的通用 应用软件进行约束和优化。