Qualitative simulation and constraint logic programming

Roy Leitch, Enrico Martinelli

Research output: Contribution to journalArticlepeer-review


The authors of this paper have investigated the potential of using the recently developed constraint logic programming (CLP) languages as an implementation engine for qualitative simulation. This was initiated by the recognition that both utilize constraints as a basic representational formalism and constraint propagation as the inference mechanism. The focus of the work was on an advanced qualitative simulation system that uses fuzzy sets to describe the values of the system variables (FuSim). This led to a number of technical innovations that allows the semi-quantitative quantity space to be represented on a finite computational domain, and an incremental algorithm that makes active (constructive) use of the constraints rather than the passive use for consistency checking employed in conventional qualitative simulation algorithms. However, the approach described is applicable to any semi-quantitative simulation system. The system, called CLP-FuSim, is implemented in the CLP language CHIP and has been tested and validated on a number of benchmark examples. The resulting performance is as least as good as the Lisp counterpart, however, the CLP version has the distinct advantage of declarative semantics and non-determinism. © 1995.

Original languageEnglish
Pages (from-to)379-390
Number of pages12
JournalEngineering Applications of Artificial Intelligence
Issue number4
Publication statusPublished - Aug 1995


  • constraint logic programming
  • fuzzy sets
  • Qualitative simulation


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