Rules as a Knowledge Representation Paradigm

  • Grzegorz J. NalepaEmail author
Part of the Intelligent Systems Reference Library book series (ISRL, volume 130)


Rules are a commonly used and natural way to express knowledge. They have been used for decades in AI, Computer Science, Cognitive Science and other domains. We start by discussing the AI roots of rules and elaborate on different kinds and types of rules. We then focus on a more careful treatment of rules in symbolic AI. There, they constitute an approach which allows for the representation of knowledge and basic automated reasoning. Originally, one of the most important areas for rule applications were expert systems. We will discuss them, along with a much broader perspective. What makes rule-based representation and reasoning particularly interesting is the opportunity for the formalization of rule languages. Therefore, selected logic-based formalizations are considered. We present in more detail a family of so-called attributive logics. Based on these concepts we introduce important requirements for a formalized description of rule based-systems.


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Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakówPoland

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