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Context in Computing pp 401–418Cite as

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.

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Notes

  1. 1.

    The mentioning of the substitution σ in Definition 25.3 is necessary in order to preserve the identity of variables in the store and its normalized version.

  2. 2.

    Most implementations of CHR are based on a multiset semantics; some implementations has an option for switching to a set semantics, but for reasons of efficiency, this is discouraged. It is recommended to use relevant simpagations for duplicate elimination as shown in the example.

  3. 3.

    The constraint solver uses a predicate “is” which is a Prolog device for arithmetic that only works when all variables in its right hand side argument are given at the time of the call. Replacing it by a proper constraint solver capable of handling equations concerning the addition and subtraction of the constant one, will make it possible to work with non-ground constraints, corresponding to calculating the robot’s position and direction relative to an unknown start position.

  4. 4.

    Abductive reasoning is often mentioned as a special case of non-monotonicity since conclusions are drawn that may not be a logical consequence of the present knowledge base. However, what we call standard semantics used in relation to abduction is a first-order, monotonic semantics for the constraint stores (knowledge bases) with a knowledge assimilation mechanism that conforms with conjunction. Readers puzzled by this discussion may find the paper (Console et al. 1991) from 1991 interesting, in which the relation between abduction and deduction is investigated in a way that has strong links to the work presented here.

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  1. Roskilde University, P.O.Box 260, 4000, Roskilde, Denmark

    Henning Christiansen

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  1. Henning Christiansen
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Correspondence to Henning Christiansen .

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  1. University Pierre and Marie Curie (UPMC), Paris, France

    Patrick Brézillon

  2. University of Central Florida, Orlando, Florida, USA

    Avelino J. Gonzalez

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Christiansen, H. (2014). Constraint Programming for Context Comprehension. In: Brézillon, P., Gonzalez, A. (eds) Context in Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1887-4_25

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  • DOI: https://doi.org/10.1007/978-1-4939-1887-4_25

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