Name: Methods for Automated Theorem Proving in Nonclassical Logics
Creator: Morgan
Keywords: Many-valued logic, 0102 computer and information sciences, 0101 mathematics, Modal logic (including the logic of norms), 01 natural sciences, Intermediate logics, Theorem proving (deduction, resolution, etc.)

Methods for automated theorem proving in nonclassical logics

descriptionPublicationkeyboard_double_arrow_right Article 01 Aug 1976Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Transactions on Computers, volume C-25, pages 852-862 (issn: 0018-9340,

Authors: Morgan;

doi: 10.1109/tc.1976.1674704

Methods for Automated Theorem Proving in Nonclassical Logics

- Summary
- Subjects
- Metrics

Abstract

In this paper we outline two basic methods for automated theorem proving in nonclassical logics, including modal, many-valued, relevance, and intuitionistic logics. We discuss advantages and disadvantages of each method and give several illustrative examples. We outline a procedure for attacking more complex problems using a combination of the two basic methods. Results of experimental applications of the techniques are reported.

Related Organizations

University of Victoria
Canada
University of Victoria
Canada

Keywords

Many-valued logic, Modal logic (including the logic of norms), Intermediate logics, Theorem proving (deduction, resolution, etc.)

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	31
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average