JISE


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Journal of Information Science and Engineering, Vol. 12 No. 1, pp. 101-125


A Category-Theoretic Treatment of Automated Theorem Proving


Maria Paola Bonacina and Jieh Hsiang#
Department of Computer Science 
University of Iowa 
Iowa City, IA 52242-1419, USA 
#Department of Computer Science 
National Taiwan University 
Taipei, Taiwan 107


    In this paper we apply category theory to investigate the mathematical structure of theorem proving derivations.
    A theorem-proving strategy is given by a set of inference rules and a search plan. Search plans have been usually described either informally (e.g., a criterion to select the next inference step) or procedurally (e.g., by giving a specific algorithm). Since both the completeness and efficiency of a theorem-proving strategy depend on the search plan, a formal, abstract treatment appears desirable. We propose an approach in this direction, that allows in particular for a precise definition of how the inference rules and the search plan cooperate to generate thederivations. Theorem-proving derivations are characterized by three essential properties: soundnessrelevance and proof reduction. We show that they are functoriality properties: these results clarify which parts of the structure of a theory a theorem-proving derivation is required to preserve. We close the paper with a comparison with related work and a discussion on further extensions of our approach.


Keywords: theorem proving, search, category theory, simplification, contraction

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