Current research projects include projects to investigate the use of multiple case representation and indexing schemes in precedent-based CBR, the effect of high level reasoning goals on supporting CBR tasks and vice versa in a mixed paradigm blackboard-based architecture, the use of CBR for generation of retrieval strategies in the context of information retrieval, and the automatic selection of parameters for dynamic scheduling problems.
In just few years, case-based reasoning has evolved from a research topic studied at a small number of specialized academic labs into an industrial-strength technology applied in various fields. The INRECA methodology presented in detail in this monograph provides a data analysis framework for developing case-based reasoning solutions for successful applications in real-world industrial contexts. The book provides a self-contained introduction to case-based reasoning applications that address both R&D professionals and general IT managers interested in this powerful new technology. In this second edition, improvements and updates have been incorporated throughout the text. Particularly useful is the systematic coverage of experience factory applications at various steps; and, of course, the references have been extended substantially.
This article presents an overview and survey of current work in case-based reasoning (CBR) integrations. There has been a recent upsurge in the integration of CBR with other reasoning modalities and computing paradigms, especially rule-based reasoning (RBR) and constraint-satisfaction problem (CSP) solving. CBR integrations with modelbased reasoning (MBR), genetic algorithms, and information retrieval are also discussed. This article characterizes the types of multimodal reasoning integrations where CBR can play a role, identifies the types of roles that CBR components can fulfill, and provides examples of integrated CBR systems.