Automated theorem proving: mapping logic into AI

  title={Automated theorem proving: mapping logic into AI},
  author={Donald W. Loveland},
  booktitle={ISMIS '86},
  • D. Loveland
  • Published in ISMIS '86 1 December 1986
  • Computer Science
Logic can be defined as the formal study of reasoning; if we replace “formal” by “mechanical” we can place almost the entire set of methodologies used in the field of automated theorem proving (ATP) within the scope of logic. Because of the goals of ATP, if not always the methodologies, ATP has been considered to be within the domain of AI. We explore the methodologies of ATP, including the logics that underlie the theorem provers, and discuss some of the mechanisms that utilize these logics… 
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Neural Unification for Logic Reasoning over Natural Language
This work proposes a new architecture, namely the Neural Unifier, and a relative training procedure, which achieves state-of-the-art results in term of generalisation, showing that mimicking a well-known inference procedure, the backward chaining, it is possible to answer deep queries even when the model is trained only on shallow ones.
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Java and Web Extensions of the Yices Little Engine of Proof
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A prolog technology theorem prover: Implementation by an extended prolog compiler
  • M. Stickel
  • Mathematics, Computer Science
    Journal of Automated Reasoning
  • 2004
A Prolog technology theorem prover (PTTP) is an extension of Prolog that is complete for the full first-order predicate calculus. It differs from Prolog in its use of unification with the occurs
A knowledge-based interactive verifier for logic programs
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Goal-Directed Context Validation for Adaptive Ubiquitous Systems
  • Chang Xu, S. Cheung, W. Chan
  • Computer Science
    International Workshop on Software Engineering for Adaptive and Self-Managing Systems (SEAMS '07)
  • 2007
A goal-directed technique to enhance the earlier link generation semantics is presented, and it is shown how the enhanced semantics helps reduce the number of generated redundant links for context validation.


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  • Mathematics, Computer Science
    Artif. Intell.
  • 1982
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  • Peter B. Andrews
  • Computer Science, Mathematics
    Computer science and applied mathematics
  • 1986
This volume will be of interest to mathematicians, computer scientists, and philosophers in universities, as well as to computer scientists in industry who wish to use higher-order logic for hardware and software specification and verification.
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