Abstraction and Hierarchical Problem Solving in Case-Based Reasoning

研究部分涉及基于案例的推理(CBR)，这是一种存储已知问题的案例及其解决方案以解决新问题的技术。由于很少有存储的案例会与新问题完全匹配，因此大多数案例最多只能与新问题进行类比。在这种情况下，首先需要检索适当的相似案例，检查它在某些基本方面是否与新问题匹配，然后以推断解决方案的方式使其适应新问题。在存储和使用案例时，有必要在存储它们以供以后使用时或在检索时进行一些抽象，以避免不得不存储大量非常相似但略有不同的案例。该项目研究了为每个存储的案例开发抽象层次结构的优势，这是一种称为“分层CBR”的技术。将分层CBR技术应用于一个典型的搜索任务(路径规划)、两个配置任务(人工产物设计和目标导向的活动规划)和一个分析任务(法律推理)，以检验关于分层CBR技术优越性的假设，并获得使用该技术的经验。在拨款期间，将制定一项教育计划，通过(1)教育本科生了解人工智能的基本方法和概念，以及人工智能的哲学、社会和认知后果，以及(2)教育其他领域的研究生了解适用于其领域的人工智能技术和工具，从而使学生接触到人工智能的洞察力、视角和工具。

The research component involves case-based reasoning (CBR) a technique that stores and later applies cases of known problems and their solutions to solve new problems. Since few stored cases will exactly match a new problem, most cases will be related at best by analogy to the new one. In that case, it is necessary first to retrieve an appropriate analogous case, check to see that it matches the new problem in some essential ways, then adapt it to the new problem in such a way as to infer a solution. In storing and using cases, it is necessary to do some abstraction, either at the time that they are stored away for later use or at the time retrieved, to avoid having to store large numbers of very similar but slightly different cases. This project examines the advantages of developing a hierarchy of abstraction for each stored case, a technique called "stratified CBR". The stratified CBR technique will be applied to a typical search task (route planning), two configuration tasks (artifact design and goal-directed activity planning), and an analytical task (legal reasoning), in order to test hypotheses about the superiority of the stratified CBR technique and to gain experience in using the technique. During the period of the grant, an educational plan will be developed that exposes students to the insights, perspectives, and tools of AI by (1) educating undergraduates about AI's basic methods and concepts and about AI's philosophical, social, and cognitive consequences, and (2) educating graduate students in other fields about the AI techniques and tools applicable to their fields.