Learning to Integrate Multiple Knowledge Sources for Case-Based Reasoning

摘要

The case-based reasoning process depends on multiple overlapping knowledge sources, each of which provides an opportunity for learning. Exploiting these opportunities requires not only determining the learning mechanisms to use for each individual knowledge source, but also how the differnet learning mechanisms interact and their combiend utility. This paper presents a case study examining the relative contributions and costs involved in learning processes for three different knowledge source--cases, case adaptation knowledge, and similarity information--in a case-based planner. It demonstrates the importance of interactions betwee ndifferent learning processes and identifies a promising method for integrating multiple learning mehtods to improve case-based reasoning.