Integrations of rule-based and case-based reasoning

Rule-based and case-based reasoning are two popular approaches used for problem solving in intelligent systems. They are natural alternatives in knowledge representation. Rules usually represent general knowledge, whereas cases encompass knowledge accumulated from specific (specialized) situations. Each approach has advantages and disadvantages. Due to their interchangeable nature, rules and cases can be easily integrated and thus produce effective knowledge representation formalisms, surpassing the disadvantages of each component method working individually. In this paper, we present a survey of approaches integrating rule-based reasoning with case-based reasoning. We describe a categorization scheme for the integrated formalisms and briefly present representative approaches of each category.