Much current CBR research focuses on how to compact, refine, and augment the contents of individual case bases, in order to distill needed information into a single concise and authoritative source. However, as deployed case-based reasoning systems become increasingly prevalent, opportunities will arise for supplementing local case bases on demand, by drawing on the case bases of other CBR systems addressing related tasks. Taking full advantage of these case bases will require multi-case-base reasoning: Reasoning not only about how to apply cases, but also about when and how to draw on particular case bases. This paper begins by considering tradeoffs of attempting to merge individual case bases into a single source, versus retaining them individually, and argues that retaining multiple case bases can benefit both performance and maintenance. However, achieving the benefits requires methods for case dispatching--deciding when to retrieve from external case bases, and which case bases to select--and for cross-case-base adaptation to revise suggested solutions from one context to apply in another. The paper presents initial experiments illustrating how these procedures may affect the benefits of using multiple case bases, and closes by delineating key research issues for multi-case-base reasoning.
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