RI: Small: Qualitative Preferences: Merging Paradigms, Extending the Language, Reasoning about Incomplete Outcomes

RI：小：定性偏好：合并范式、扩展语言、推理不完整的结果

• 批准号: 0913459
• 负责人: Miroslaw Truszczynski
• 金额: $ 38.5万
• 依托单位: University of Kentucky Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0913459&HistoricalAwards=false
• 关键词: RI; Small; Qualitative; Preferences; Merging

The most common approach in decision theory involves preferences expressed numerically in terms of utility functions, while optimization over different choices takes into account the probability distribution over possible states of the world. An alternative approach represents preferences in qualitative terms, and is motivated, in part, by difficulties in building good utility functions, ascertaining accurate probability distributions, and related problems.This project is advancing qualitative decision theory by focusing on two promising formalisms for representing and reasoning about qualitative preferences: conditional preference networks (CP-nets) and answer-set optimization (ASO) programs. Both CP-nets and ASO programs offer representations for several classes of preference problems, but each has major limitations. This project addresses these limitations by developing a formalism. ASO(CP) programs, which extend both ASO programs and CP-nets by exploiting key properties of both. The project's major objectives are: to introduce formally ASO(CP) programs by integrating into ASO programs generalized conditional (ceteris paribus) preferences of CP-nets; to establish expressivity of ASO(CP) programs, to study properties of preorders that can be defined by means of ASO(CP) programs, and to address relevant computational issues; to investigate a crucial problem of preference equivalence, essential for automated preference manipulation; to study an extension of ASO(CP) programs to the case of incompletely specified outcomes, essential for practical applications; and, to extend ASO(CP) programs to the first-order language extended with aggregate operators.Representing preferences qualitatively and optimizing over such preferences is a fundamental problem of qualitative decision theory. By integrating and advancing understanding of major types of common preferences that are captured by ASO programs and CP-nets, this project will produce theoretical and practical advances in representation and reasoning about preferences, bringing it to the point where it can be effectively used in practical decision support systems.

决策理论中最常见的方法涉及用效用函数表示的数值偏好，而不同选择的优化则考虑了世界可能状态的概率分布。另一种方法表示的偏好在定性方面，是动机，部分是困难的，在建立良好的效用函数，确定准确的概率分布，以及相关的problems.This项目是推进定性决策理论，专注于两个有前途的形式主义表示和推理的定性偏好：条件偏好网络（CP-网）和答案集优化（阿索）程序。CP网和阿索程序都提供了几类偏好问题的表示，但各自都有很大的局限性。本项目通过开发一种形式主义来解决这些限制。阿索（CP）程序，通过利用两者的关键属性来扩展阿索程序和CP-网。该项目的主要目标是：正式介绍阿索（CP）程序，通过整合到阿索程序广义条件（ceteris paribus）偏好的CP-网;建立表达的阿索（CP）程序，研究属性的前序，可以定义的阿索（CP）程序，并解决相关的计算问题;研究偏好等价的一个关键问题，这是自动偏好操纵的关键;研究阿索（CP）程序对不完全指定结果的扩展，这是实际应用的关键;定性地表示偏好和优化偏好是定性决策理论的一个基本问题。通过整合和推进对阿索程序和CP网络捕获的主要常见偏好类型的理解，该项目将在偏好的表示和推理方面产生理论和实践上的进步，使其能够有效地用于实际决策支持系统。