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.

这个项目解决了问题解决的一个方面，这对机器和人类都很关键：通过相关先例进行类比推理。拟议的研究的目标是一个基于先例的类比推理的计算模型，使用一个简单的，但表达和认知上合理的一套表示，捕捉知识的实体，类，原因，价值观，以及沿着真实的和抽象的轨迹运动。该项目的目标领域是政治学，在情报分析、国际关系和政府政策等领域，专家们使用这种基于案例的推理来分析、评估，并根据相关的过去经验对新情况提出建议。该项目建立在NSF赞助的桥梁系统中开始的类比研究的基础上，将利用专家分析的有据可查的政治情景和类比的集合。虽然这个项目的重点主要是发展一个计算理论的推理类比从经验，将建立一个原型工具，旨在帮助分析师负责评估行动方案，解决一个重要方面的分析专业知识：检测意外后果的能力与先例推理。这个原型的“错误阻止器”组件将监控情况和建议的行动，将这些与先例数据库相匹配，并且如果合适的话，建议分析师检查相关的先例，以寻找可能被忽视的先例所建议的可能性。为了解决计算机科学和社会科学都感兴趣的问题，该项目将有助于一般基于先例的推理理论，特别是政治科学中的行动分析过程。