p-95-11 Learning to Improve Case Adaptation by Introspective Reasoning and CBR David Leake and Andrew Kinley and David Wilson Proceedings of the First International Conference on Case-Based Reasoning, Sesimbra, Portugal, 1995. In press. Abstract In current CBR systems, case adaptation is usually performed by rule-based methods that use task-specific rules hand-coded by the system developer. The ability to define those rules depends on knowledge of the task and domain that may not be available a priori, presenting a serious impediment to endowing CBR systems with the needed adaptation knowledge. This paper describes ongoing research on a method to address this problem by acquiring adaptation knowledge from experience. The method uses reasoning from scratch, based on introspective reasoning about the requirements for successful adaptation, to build up a library of adaptation cases that are stored for future re-use. We describe the tenets of the approach and the types of knowledge it requires. We sketch initial computer implementation, lessons learned, and open questions for further study. A postscript file for the full paper is available electronically. To get a copy by anonymous ftp, see ftp://ftp.cs.indiana.edu/pub/leake/README. on the web, open URL ftp://ftp.cs.indiana.edu/pub/leake/INDEX.html.