David B. Leake and Andrew Kinley
Multimodal reasoning systems can improve the effectiveness of reasoning by integrating multiple reasoning methods, each selectively applied to the tasks for which it is best-suited. One integration approach is to bring CBR into other systems, by developing case-based intelligent components [Riesbeck 96] that collaborate with other reasoning systems, monitoring their successes and failures and suggesting solutions when prior experiences are relevant. Another approach is to bring other reasoning processes into a CBR system’s own architecture, to facilitate subprocesses of CBR such as case adaptation and similarity assessment. This paper describes a project combining both approaches: It discusses motivations and methods for a case-based components approach to integrating multiple reasoning modes, styles, and levels within a case-based reasoning system. The fundamental principle is for the system to use case-based components to learn by monitoring, capturing, and exploiting traces of multiple types of prior reasoning within the CBR system. The paper considers the benefits of this approach for improving CBR and its potential applicability to integrations in other contexts.