Constraint Programming for Context Comprehension

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Abstract

A close similarity is demonstrated between context comprehension, such as discourse analysis, and constraint programming. The constraint store takes the role of a growing knowledge base learned throughout the discourse, and a suitable constraint solver does the job of incorporating new pieces of knowledge. The language of Constraint Handling Rules, CHR, is suggested for defining constraint solvers that reflect “world knowledge” for the given domain, and driver algorithms may be expressed in Prolog or additional rules of CHR. It is argued that this way of doing context comprehension is an instance of abductive reasoning. The approach fits with possible worlds semantics that allows both standard first-order and non-monotonic semantics.

Keywords

Logic Programming Integrity Constraint Constraint Solver Standard Semantic Constraint Logic Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Roskilde UniversityRoskildeDenmark

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