EAGER: Decision Support System for Reasoning with Preferences

EAGER：带有偏好的推理决策支持系统

• 批准号: 1143734
• 负责人: Samik Basu
• 金额: $ 11.14万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1143734&HistoricalAwards=false
• 关键词: EAGER; Decision; Support; System; Reasoning

Automated decision support systems help users make informed and intelligent choices over a set of alternatives, taking into account user preferences and trade-offs among multiple system attributes. In the software engineering domain decision support systems are used to help in evaluating alternative design, technical and managerial choices in terms of quantitative preferences and trade-offs. Preferences over alternatives are evaluated either by directly soliciting from the stakeholders a measure of the perceived utility/value of each attribute, or by quantifying such utility/value based on past experience and expertise. In most practical settings, however, preferences over attributes cannot all be quantified. On the other hand, considering preferences only qualitatively (specifying them as simple relative orderings between alternatives) is also not practical. To overcome these limitations, the proposed research focuses on developing a new paradigm for decision support systems, where preferences are specified both in qualitative and quantitative terms.The main thrust of this work will be to: (a) develop robust formalisms for representing and reasoning with quantitative and qualitative preferences in an unified fashion, (b) investigate application-domain specific extensions to the formalisms, and (c) identify implementation strategies for practical application of the decision support system as a preference analyzer. The anticipated results will help realize application-specific robust decision support systems in multiple domains, including product-line engineering, safety-critical system development, and goal-oriented requirements engineering, by enabling improved automated reasoning about preferences. This work will contribute to research-based training of a postdoctoral scholar and a graduate student in techniques that cut across software engineering, formal methods and artificial intelligence. Research results will be disseminated through publications in journals and conferences.

自动化决策支持系统帮助用户在一组备选方案中做出明智和智能的选择，同时考虑到用户的偏好和多个系统属性之间的权衡。在软件工程领域，决策支持系统被用来帮助评估替代设计，技术和管理选择的定量偏好和权衡。对备选方案的偏好进行评估的方法是，直接向利益相关者征求对每个属性的感知效用/价值的衡量，或者根据过去的经验和专业知识量化这种效用/价值。然而，在大多数实际情况下，对属性的偏好不能全部量化。另一方面，只定性地考虑偏好（将它们指定为选项之间的简单相对排序）也是不切实际的。为了克服这些局限性，拟议的研究集中于为决策支持系统开发一种新的模式，在这种模式中，偏好在定性和定量方面都被指定。这项工作的主要目的是：（a）开发用于以统一的方式用定量和定性偏好进行表示和推理的鲁棒形式体系，（B）研究对形式体系的应用领域特定扩展，以及（c）识别用于将决策支持系统作为偏好分析器的实际应用的实现策略。预期的结果将有助于实现特定于应用程序的强大的决策支持系统在多个领域，包括产品线工程，安全关键系统的开发，和面向目标的需求工程，使改进的自动推理的偏好。 这项工作将有助于对博士后学者和研究生进行跨软件工程，正式方法和人工智能技术的研究培训。研究成果将通过在期刊和会议上发表的出版物传播。