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In computer science, a rule-based system is used to store and manipulate knowledge to interpret information in a useful way. It is often used in artificial intelligence applications and research.

Normally, the term rule-based system is applied to systems involving human-crafted or curated rule sets. Rule-based systems constructed using automatic rule inference, such as rule-based machine learning, are normally excluded from this system type.


A classic example of a rule-based system is the domain-specific expert system that uses rules to make deductions or choices.[1] For example, an expert system might help a doctor choose the correct diagnosis based on a cluster of symptoms, or select tactical moves to play a game.

Rule-based systems can be used to perform lexical analysis to compile or interpret computer programs, or in natural language processing.[2]

Rule-based programming attempts to derive execution instructions from a starting set of data and rules. This is a more indirect method than that employed by an imperative programming language, which lists execution steps sequentially.


A typical rule-based system has four basic components:[3]

  • Match: In this first phase, the left-hand sides of all productions are matched against the contents of working memory. As a result a conflict set is obtained, which consists of instantiations of all satisfied productions. An instantiation of a production is an ordered list of working memory elements that satisfies the left-hand side of the production.
  • Conflict-Resolution: In this second phase, one of the production instantiations in the conflict set is chosen for execution. If no productions are satisfied, the interpreter halts.
  • Act: In this third phase, the actions of the production selected in the conflict-resolution phase are executed. These actions may change the contents of working memory. At the end of this phase, execution returns to the first phase.

See also


  1. ^ Crina Grosan; Ajith Abraham (29 July 2011). Intelligent Systems: A Modern Approach. Springer Science & Business Media. pp. 149–. ISBN 978-3-642-21004-4.
  2. ^ Sin-Wai Chan (13 November 2014). Routledge Encyclopedia of Translation Technology. Routledge. pp. 454–. ISBN 978-1-317-60815-8.
  3. ^ "What is a rule-based system?".
  4. ^ Cabitza, F., & Dal Seno, B. (2005). "DJess-A Knowledge-Sharing Middleware to Deploy Distributed Inference Systems". International Journal of Computer and Information Engineering. 2: 66–69. doi:10.1109/PERSER.2005.1506416. S2CID 27323155.((cite journal)): CS1 maint: multiple names: authors list (link)