1. 1999/3/10Li-we Pan1 Case-Based CBR : Capturing and Reusing Reasoning About Case Adaptation 指導老師 ： 何正信教授 學生：潘立偉 學號： M8702048 日期： 88/3/10 David B. Leake, Andrew Kinley,& David Wilson International Journal of Expert Systems, 1997, Vol10, No2 p197~213

2. 1999/3/10Li-we Pan2 Why need case-based CBR CBR is receiving widespread use in applications, especially in “retrieve and propose” advisory system. Is difficult in choose a method for poorly-understand domain The difficulty of codifying the domain may also make it impractical to build the rule-based systems usually used for case adaptation : the deep knowledge required to adapt cases may be precisely the same knowledge the would be needed to reason form scratch.

3. 1999/3/10Li-we Pan3 Case-based CBR The framework integrates case-based adaptation into the CBR system. As an “intelligent component” that automatically records and reapplies adaptations that the system initially performs form scratch. Uses derivational analogy to store and replay the reasoning. Develop method to monitor, record, and reapply traces of its own reasoning.

4. 1999/3/10Li-we Pan4 Using ‘Introspective reasoning’-reasoning and learning about the reasoning process Acquires adaptation knowledge form experience with autonomous adaptation and by interactively capturing the adaptation process of a human user. The questions of case-based CBR –System design –Knowledge acquisition –Effectiveness of learning

5. 1999/3/10Li-we Pan5 A study of case-based adaptation Ex : DIAL disaster response for natural and man-made disasters. Include –schema-based story understander process input –response plan retriever –simple evaluator for candidate response plans –*adaptation component to adapt retrieved plans

6. 1999/3/10Li-we Pan6 Basic sequence of processing step Case-based adaptation Rule-based adaptation(introspective planning) Plan evaluation Storage

7. 1999/3/10Li-we Pan7 Acquiring adaptation cases How a cased-based adaptation component can capture autonomous adaptations from the CBR system’s own experience with adaptations performed form scratch How the cased-based adaptation component’s case library can be augmented by capturing the sequence of steps in a user’s cases adaptation process How the system’s adaptation process can be redirected interactively through a simple interactive interface

8. 1999/3/10Li-we Pan8 Capture autonomous adaptations Starts with general rules about information search and about the constraints that must be satisfied by the case adaptation process. Store the trace of reasoning done Ex: schoolchildren do not have union.

9. 1999/3/10Li-we Pan9 Initial rule-based adaptation process provide –flexibility to deal with novel adaptation problems –a way to generate specific adaptation knowledge Rule-based adaptation process treats the adaptation problem as primarily one of finding the information needed to apply a set of very general transformations-substitutions, deletions, and additions to the structure of a retrieval solution-by search memory

10. 1999/3/10Li-we Pan10 Capture user adaptations Use the derivational approach to adaptation as the basis for an interface to facilitate direct acquisition of adaptation cases for a human user Have 3 problems cause adaptation to fail –Resource limit exceeded –Overspecific constraints –Overgeneral constraints

11. 1999/3/10Li-we Pan11 Perspective on case-based adaptation Design choose –transformational vs. derivational CBR –case representation –case organization –adaptation of adaptation cased knowledge acquisition effort

12. 1999/3/10Li-we Pan12 effects on adaptation efficiency –adaptation learning can be important as case learning –simple domain-independent methods can be sufficient for case-based CBR processes comparison to other method for addressing the adaptation problem. Ramifications of adaptation learning for case-based maintenance