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A prolog-like inference system for computing minimum-cost abductive explanations in natural-language interpretation

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Abstract

By determining what added assumptions would suffice to make the logical form of a sentence in natural language provable, abductive inference can be used in the interpretation of sentences to determine what information should be added to the listener's knowledge, i.e., what he should learn from the sentence. This is a comparatively new application of mechanized abduction. A new form of abduction — least specific abduction — is proposed as being more appropriate to the task of interpreting natural language than the forms that have been used in the traditional diagnostic and design-synthesis applications of abduction. The assignment of numerical costs to axioms and assumable literals permits specification of preferences on different abductive explanations. A new Prolog-like inference system that computes abductive explanations and their costs is given. To facilitate the computation of minimum-cost explanations, the inference system, unlike others such as Prolog, is designed to avoid the repeated use of the same instance of an axiom or assumption.

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Authors and Affiliations

  1. Artificial Intelligence Center, SRI International, 333 Ravenswood Avenue, 94025, Menlo Park, CA, USA

    Mark E. Stickel

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  1. Mark E. Stickel
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This research is supported by the Defense Advanced Research Projects Agency, under Contract N00014-85-C-0013 with the Office of Naval Research, and by the National Science Foundation, under Grant CCR-8611116. The views and conclusions contained herein are those of the author and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency, the National Science Foundation, or the United States government.

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Stickel, M.E. A prolog-like inference system for computing minimum-cost abductive explanations in natural-language interpretation. Ann Math Artif Intell 4, 89–105 (1991). https://doi.org/10.1007/BF01531174

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