Idealization-Based Discovery of Search Heuristics

基于理想化的搜索启发式发现

• 批准号: 9017121
• 负责人: David Mostow
• 金额: $ 13.37万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-09-01 至 1994-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9017121&HistoricalAwards=false
• 关键词: Idealization; Based; Discovery; Search; Heuristics

Many computational problems can be solved by searching through a well-defined but huge space of candidates provided good heuristics are available to guide the search. Thus automated discovery of search heuristics would have both practical and scientific importance. In this approach, the generation of heuristics is modelled as the application of successive transformations to an initial problem specification. This research addresses a number of issues raised by the long-term goal of scaling up to more realistic application domains. To refine the model, studies of perturbation experiments aimed at understanding when and why it works will be carried out. To enrich the space of generated heuristics, extensions and integration of transformations so as to rederive known scheduling and routing heuristics and the discovery of new ones will be undertaken. To explore this space more efficiently, novel methods for evaluating potential heuristics will be employed. Expected outcomes of this work include engineering advances in automated methods for discovering heuristics, as well as scientific advances in understanding their underlying principles.

许多计算问题可以通过搜索 明确但巨大的候选人空间提供了良好的 我们有专家来指导搜索。 从而实现自动化 搜索引擎的发现将具有实用性和 科学的重要性。 在这种方法中， 物流学被建模为应用连续的 转换为初始问题规范。 这 研究解决了长期以来提出的一些问题， 目标是扩展到更现实的应用领域。 到 完善模型，研究微扰实验，旨在 了解何时以及为什么它会起作用。 到 丰富了生成的语法、扩展和 集成变换以便重新导出已知调度 和路由算法以及新算法的发现 进行。 为了更有效地探索这个空间， 将采用评估潜在竞争力的方法。 这项工作的预期成果包括以下方面的工程进步 自动化的方法来发现电子邮件，以及 在理解其基本原理方面的科学进步。