Abstract
This paper illustrates two applications of the case-based reasoning methodology (CBR) to the forest fire emergencies application domain. The first application is an interactive planning system used for planning the initial attack on forest fires. Our planning approach is built on the integration of case-based reasoning and constraint reasoning. Case-based reasoning plays the role of assumption maker, suggesting old solution to similar situation, and constraint reasoning filters those assumption in a feasible solution. The second application combines case-based reasoning and knowledge-discovering techniques to help both teachers and students to acquire the knowledge contained in a case base of past interventions. Manipulation, browsing and enquiring tools enable users to directly extract knowledge in the form of: feature mutual dependencies; clusters and prototypes existing in the case base; feature statistical descriptors; results of CBR queries.