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In complex domains, it is often necessary to determine which reasoning method would be the most appropriate for each task, and a combination of different methods has often shown the best results. We examine how two complementary reasoning methods, case-based reasoning and Bayesian networks, can be combined using metareasoning to form a more robust and better-performing system.
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