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Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description)

PyRes is a complete theorem prover for classical first-order logic. It is not designed for high performance, but to clearly demonstrate the core concepts of a saturating theorem prover. The system is written in extensively commented Python, explaining data structures, algorithms, and many of the und...

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Detalles Bibliográficos
Autores principales: Schulz, Stephan, Pease, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7324010/
http://dx.doi.org/10.1007/978-3-030-51054-1_9
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author Schulz, Stephan
Pease, Adam
author_facet Schulz, Stephan
Pease, Adam
author_sort Schulz, Stephan
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description PyRes is a complete theorem prover for classical first-order logic. It is not designed for high performance, but to clearly demonstrate the core concepts of a saturating theorem prover. The system is written in extensively commented Python, explaining data structures, algorithms, and many of the underlying theoretical concepts. The prover implements binary resolution with factoring and optional negative literal selection. Equality is handled by adding the basic axioms of equality. PyRes uses the given-clause algorithm, optionally controlled by weight- and age evaluations for clause selection. The prover can read TPTP CNF/FOF input files and produces TPTP/TSTP proof objects. Evaluation shows, as expected, mediocre performance compared to modern high-performance systems, with relatively better performance for problems without equality. However, the implementation seems to be sound and complete.
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spelling pubmed-73240102020-06-30 Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description) Schulz, Stephan Pease, Adam Automated Reasoning Article PyRes is a complete theorem prover for classical first-order logic. It is not designed for high performance, but to clearly demonstrate the core concepts of a saturating theorem prover. The system is written in extensively commented Python, explaining data structures, algorithms, and many of the underlying theoretical concepts. The prover implements binary resolution with factoring and optional negative literal selection. Equality is handled by adding the basic axioms of equality. PyRes uses the given-clause algorithm, optionally controlled by weight- and age evaluations for clause selection. The prover can read TPTP CNF/FOF input files and produces TPTP/TSTP proof objects. Evaluation shows, as expected, mediocre performance compared to modern high-performance systems, with relatively better performance for problems without equality. However, the implementation seems to be sound and complete. 2020-06-06 /pmc/articles/PMC7324010/ http://dx.doi.org/10.1007/978-3-030-51054-1_9 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Schulz, Stephan
Pease, Adam
Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description)
title Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description)
title_full Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description)
title_fullStr Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description)
title_full_unstemmed Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description)
title_short Teaching Automated Theorem Proving by Example: PyRes 1.2: (System Description)
title_sort teaching automated theorem proving by example: pyres 1.2: (system description)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7324010/
http://dx.doi.org/10.1007/978-3-030-51054-1_9
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