Representationally Complete Analogical - Reasoning Systems and Steps Toward Their Application in Political Science

代表性完整的类比推理系统及其在政治学中的应用步骤

• 批准号: 0413206
• 负责人: Patrick Winston
• 金额: $ 44.64万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-01 至 2008-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0413206&HistoricalAwards=false
• 关键词: Representationally; Complete; Analogical; Reasoning; Systems

This project addresses an aspect of problem solving that is key for both machines and humans: reasoning by analogy with relevant precedents. The goal of the proposed research is a computational model of precedent-based analogical reasoning using a simple but expressive and cognitively plausible suite of representations that capture knowledge about entities, classes, causes, values, and motion along real and abstract trajectories. The project's target domain is political science, where in areas such as intelligence analysis, international relations, and government policy, experts use this type of case-based reasoning to analyze, assess, and make recommendations about new situations based on relevant past experience. The project, which builds on analogy research begun in the NSF-sponsored Bridge System, will make use of collections of well-documented political scenarios and analogies that have been analyzed by experts. While this project focuses primarily on development of a computational theory about reasoning by analogy from experience, a prototype tool will be built that is intended to assist analysts charged with evaluating courses of action by addressing an important aspect of analytical expertise: the ability to detect unintended consequences with precedential reasoning. This "blunder stopper" component of the prototype will monitor situations and proposed actions, match these against a data base of precedents, and, if appropriate, advise the analyst to examine a relevant precedent for possibilities suggested by the precedent that might otherwise be overlooked. In addressing a problem of interest to both computer science and social science, this project will contribute to theories of precedent-based reasoning in general, and course of action analysis in political science in particular.

该项目解决了对机器和人类都至关重要的问题解决的一个方面：通过与相关先例进行类比推理。拟议研究的目标是基于先例的类比推理的计算模型，使用简单但富有表现力且认知上合理的表示套件来捕获有关实体、类、原因、值以及沿着真实和抽象轨迹的运动的知识。该项目的目标领域是政治科学，在情报分析、国际关系和政府政策等领域，专家利用这种基于案例的推理，根据过去的相关经验对新情况进行分析、评估和提出建议。该项目建立在美国国家科学基金会资助的桥梁系统中开始的类比研究的基础上，将利用专家分析过的有据可查的政治情景和类比集合。虽然该项目主要侧重于开发关于根据经验进行类比推理的计算理论，但将构建一个原型工具，旨在通过解决分析专业知识的一个重要方面来帮助负责评估行动方案的分析师：检测意外的能力具有先例推理的后果。原型的这个“错误阻止器”组件将监视情况和拟议的行动，将它们与先例数据库进行匹配，并在适当的情况下建议分析师检查相关先例，以了解先例所暗示的可能被忽视的可能性。在解决计算机科学和社会科学都感兴趣的问题时，该项目将为基于先例的推理理论做出贡献，特别是政治学中的行动分析过程。