Decision-Theoretic and Symbolic Planning

决策理论和符号规划

• 批准号: 9207262
• 负责人: Peter Haddawy
• 金额: $ 11.74万
• 依托单位: University of Wisconsin-Milwaukee
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-07-15 至 1995-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9207262&HistoricalAwards=false
• 关键词: Decision; Theoretic; Symbolic; Planning

As AI planning systems are applied to more realistic problems, the issue of choosing among alternative plans arises. The planner typically cannot prove that any alternative will or will not be successful, and so it much choose among plans on the basis of how likely they are to achieve their aims and how efficiently they do so. Decision theory supplies a normative model for making these choices, but is not directly applicable to the planning problem as AI has posed it, and more importantly does not provide a computational framework within which to make the choices. In particular, decision theory offers no advice on how to generate or modify plans. Decision theory and symbolic AI planning algorithms therefore offer complementary strengths: the former provides a rich representation for expressing choice among alternatives and a theory of how to make those choices rationally; the latter provides a computational method for generating and improving plans, but under restrictive assumptions. The two approaches will be integrated to produce a practical decision-theoretic planner. The research contains theoretical and computational; aspects, the former oriented toward reconciling the decision-theoretic and AI problem representations, the latter oriented toward developing an algorithm that efficiently builds, evaluated, and chooses among plan alternatives.

当人工智能规划系统应用于更现实的问题时，在备选方案中进行选择的问题就出现了。计划者通常无法证明任何选择是否会成功，因此，他们只能根据计划实现目标的可能性和效率来选择计划。决策理论为做出这些选择提供了一个规范的模型，但并不像人工智能所提出的那样直接适用于规划问题，更重要的是，它没有提供一个做出选择的计算框架。特别是，决策理论没有提供关于如何生成或修改计划的建议。因此，决策理论和符号人工智能规划算法提供了互补的优势：前者提供了丰富的表征来表达选项之间的选择，以及如何理性地做出这些选择的理论；后者提供了一种生成和改进计划的计算方法，但在限制性假设下。这两种方法将被整合以产生一个实用的决策理论规划器。研究内容包括理论研究和计算研究；方面，前者面向协调决策理论和人工智能问题表示，后者面向开发一种有效构建、评估和选择方案的算法。