Relevant bibliographies by topics / Automated theorem proving

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Automated theorem proving'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Automated theorem proving"

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Crouse, Maxwell, Ibrahim Abdelaziz, Bassem Makni, et al. "A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 7 (2021): 6279–87. http://dx.doi.org/10.1609/aaai.v35i7.16780.

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Automated theorem provers have traditionally relied on manually tuned heuristics to guide how they perform proof search. Deep reinforcement learning has been proposed as a way to obviate the need for such heuristics, however, its deployment in automated theorem proving remains a challenge. In this paper we introduce TRAIL, a system that applies deep reinforcement learning to saturation-based theorem proving. TRAIL leverages (a) a novel neural representation of the state of a theorem prover and (b) a novel characterization of the inference selection process in terms of an attention-based action
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Plaisted, David A. "Automated theorem proving." Wiley Interdisciplinary Reviews: Cognitive Science 5, no. 2 (2014): 115–28. http://dx.doi.org/10.1002/wcs.1269.

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Nossum, Rolf. "Automated theorem proving methods." BIT 25, no. 1 (1985): 51–64. http://dx.doi.org/10.1007/bf01934987.

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RUSSELL, STEPHEN, and TRACI WHEELER UNISYS. "On Automated Theorem Proving." Annals of the New York Academy of Sciences 661, no. 1 Frontiers of (1992): 160–73. http://dx.doi.org/10.1111/j.1749-6632.1992.tb26040.x.

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KANSO, KARIM, and ANTON SETZER. "A light-weight integration of automated and interactive theorem proving." Mathematical Structures in Computer Science 26, no. 1 (2014): 129–53. http://dx.doi.org/10.1017/s0960129514000140.

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In this paper, aimed at dependently typed programmers, we present a novel connection between automated and interactive theorem proving paradigms. The novelty is that the connection offers a better trade-off between usability, efficiency and soundness when compared to existing techniques. This technique allows for a powerful interactive proof framework that facilitates efficient verification of finite domain theorems and guided construction of the proof of infinite domain theorems. Such situations typically occur with industrial verification. As a case study, an embedding of SAT and CTL model c
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Pastre, Dominique. "Automated theorem proving in mathematics." Annals of Mathematics and Artificial Intelligence 8, no. 3-4 (1993): 425–47. http://dx.doi.org/10.1007/bf01530801.

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WOLF, ANDREAS, and REINHOLD LETZ. "STRATEGY PARALLELISM IN AUTOMATED THEOREM PROVING." International Journal of Pattern Recognition and Artificial Intelligence 13, no. 02 (1999): 219–45. http://dx.doi.org/10.1142/s0218001499000136.

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Automated theorem provers use search strategies. Unfortunately, there is no unique strategy which is uniformly successful on all problems. This motivates us to apply different strategies in parallel, in a competitive manner. In this paper, we discuss properties, problems, and perspectives of strategy parallelism in theorem proving. We develop basic concepts like the complementarity and the overlap value of strategy sets. Some of the problems such as initial strategy selection and run-time strategy exchange are discussed in more detail. The paper also contains the description of an implementati
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Elias, Joran. "Automated Geometric Theorem Proving: Wu's Method." Mathematics Enthusiast 3, no. 1 (2006): 3–50. http://dx.doi.org/10.54870/1551-3440.1034.

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Windsteiger, Wolfgang. "Automated Theorem Proving in the Classroom." Electronic Proceedings in Theoretical Computer Science 352 (December 30, 2021): 54–63. http://dx.doi.org/10.4204/eptcs.352.6.

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Peikert, R. "Automated theorem proving: the resolution method." ACM SIGSAM Bulletin 21, no. 3 (1987): 61–68. http://dx.doi.org/10.1145/29309.29319.

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Dissertations / Theses on the topic "Automated theorem proving"

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Kakkad, Aman. "Machine Learning for Automated Theorem Proving." Scholarly Repository, 2009. http://scholarlyrepository.miami.edu/oa_theses/223.

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Developing logic in machines has always been an area of concern for scientists. Automated Theorem Proving is a field that has implemented the concept of logical consequence to a certain level. However, if the number of available axioms is very large then the probability of getting a proof for a conjecture in a reasonable time limit can be very small. This is where the ability to learn from previously proved theorems comes into play. If we see in our own lives, whenever a new situation S(NEW) is encountered we try to recollect all old scenarios S(OLD) in our neural system similar to the new one
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Folkler, Andreas. "Automated Theorem Proving : Resolution vs. Tableaux." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5531.

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The purpose of this master thesis was to investigate which of the two methods, resolution and tableaux, that is the most appropriate for automated theorem proving. This was done by implementing an automated theorem prover, comparing and documenting implementation problems, and measuring proving efficiency. In this thesis, I conclude that the resolution method might be more suitable for an automated theorem prover than tableaux, in the aspect of ease of implementation. Regarding the efficiency, the test results indicate that resolution is the better choice.<br>Syftet med detta magisterarbete va
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Bridge, J. P. "Machine learning and automated theorem proving." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.596901.

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Computer programs to find formal proofs of theorems were originally designed as tools for mathematicians, but modern applications are much more diverse. In particular they are used in formal methods to verify software and hardware designs to prevent errors being introduced into systems. Despite this, the high level of human expertise required in their use means that theorem proving tools are not widely used by non-specialists. The work described in this dissertation addresses one aspect of this problem, that of heuristic selection. In theory theorem provers should be automatic; in practice the
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Haufe, Sebastian. "Automated Theorem Proving for General Game Playing." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-89998.

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While automated game playing systems like Deep Blue perform excellent within their domain, handling a different game or even a slight change of rules is impossible without intervention of the programmer. Considered a great challenge for Artificial Intelligence, General Game Playing is concerned with the development of techniques that enable computer programs to play arbitrary, possibly unknown n-player games given nothing but the game rules in a tailor-made description language. A key to success in this endeavour is the ability to reliably extract hidden game-specific features from a given gam
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Prince, Rawle C. S. "Aspects of the theory of containers within automated theorem proving." Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/11793/.

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This thesis explores applications of the theory of containers within automated theorem proving. Container theory provides a foundational analysis of data types as containers, specified by a type $S$ of shapes and a function P assigning to each shape its set of positions for data.More importantly, a representation theorem guarantees that polymorphic functions between container data types are given by container morphisms, which are characterised by mappings between shapes and positions. Container theory is interesting, in this context, for the following reasons. A mechanism for representing and
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Gottliebsen, Hanne. "Automated theorem proving for mathematics : real analysis in PVS." Thesis, University of St Andrews, 2002. http://hdl.handle.net/10023/15046.

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Computer Algebra Systems (CASs), such as Maple and Mathematica, are now widely used in both industry and education. In many areas of mathematics they perform well. However, many well-established methods in mathematics, such as definite integration via the fundamental theorem of calculus, rely on analytic side conditions which CASs in general do not support. This thesis presents our work with automatic, formal mathematics using the theorem prover PVS. Based on an existing real analysis library for PVS, we have implemented transcendental functions such as exp, cos, sin, tan and their inverses, a
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Araragi, Tadashi. "Applications of automated theorem proving methods to multi-agent systems." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/143884.

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Goble, Tiffany Danielle. "Automate Reasoning: Computer Assisted Proofs in Set Theory Using Godel's Algorithm for Class Formation." Thesis, Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4767.

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Automated reasoning, and in particular automated theorem proving, has become a very important research field within the world of mathematics. Besides being used to verify proofs of theorems, it has also been used to discover proofs of theorems which were previously open problems. In this thesis, an automated reasoning assistant based on Godel's class theory is used to deduce several theorems.
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Almulla, Mohammed Ali. "Analysis of the use of semantic trees in automated theorem proving." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=28662.

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Semantic trees have served as a theoretical tool for confirming the unsatisfiability of clauses in first-order predicate logic, but it has seemed impractical to use them in practice. In this thesis we experimentally investigated the practicality of generating semantic trees for proofs of unsatisfiability. We considered two ways of generating semantic trees. First, we looked at semantic trees generated using the canonical enumeration of atoms from the Herbrand base of the given clauses. Then, we considered semantic trees generated by selectively choosing the atoms from the Herbrand base using a
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Johnson, Robert David. "Parallel analytic tableaux systems." Thesis, Queen Mary, University of London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362777.

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Books on the topic "Automated theorem proving"

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Bibel, Wolfgang. Automated Theorem Proving. Vieweg+Teubner Verlag, 1987. http://dx.doi.org/10.1007/978-3-322-90102-6.

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Newborn, Monty. Automated Theorem Proving. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0089-2.

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Bibel, W. Automated theorem proving. 2nd ed. F. Vieweg, 1987.

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Johnson, Christopher Andrew. Topics in automated theorem proving. typescript, 1989.

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Schumann, Johann M. Automated Theorem Proving in Software Engineering. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-22646-9.

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Fitting, Melvin. First-order logic and automated theorem proving. 2nd ed. Springer, 1996.

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Fitting, Melvin. First-Order Logic and Automated Theorem Proving. Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-0357-2.

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Fitting, Melvin. First-Order Logic and Automated Theorem Proving. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2360-3.

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Fitting, Melvin. First-order logic and automated theorem proving. Springer-Verlag, 1990.

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Fitting, Melvin. First-Order Logic and Automated Theorem Proving. Springer New York, 1996.

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Book chapters on the topic "Automated theorem proving"

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Stachniak, Zbigniew. "Theorem Proving Strategies." In Automated Reasoning Series. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-1677-7_5.

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Li, Hongbo. "Automated Theorem Proving." In Geometric Algebra with Applications in Science and Engineering. Birkhäuser Boston, 2001. http://dx.doi.org/10.1007/978-1-4612-0159-5_6.

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Dowek, Gilles. "Automated Theorem Proving." In Proofs and Algorithms. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-121-9_6.

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Baelde, David, Dale Miller, and Zachary Snow. "Focused Inductive Theorem Proving." In Automated Reasoning. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14203-1_24.

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Newborn, Monty. "Theo:A Resolution—Refutation Theorem Prover." In Automated Theorem Proving. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0089-2_9.

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Newborn, Monty. "Herby: A Semantic—Tree Theorem Prover." In Automated Theorem Proving. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0089-2_7.

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Newborn, Monty. "The Cade Atp System Competitions and Other Theorem Provers." In Automated Theorem Proving. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0089-2_13.

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Newborn, Monty. "A Brief Introduction to Compile, Herby, and Theo." In Automated Theorem Proving. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0089-2_1.

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Newborn, Monty. "Using Theo." In Automated Theorem Proving. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0089-2_10.

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Newborn, Monty. "A Look at the Source Code of Herby." In Automated Theorem Proving. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0089-2_11.

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Conference papers on the topic "Automated theorem proving"

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Lama, Vanessa, Catherine Ma, and Tirthankar Ghosal. "Benchmarking Automated Theorem Proving with Large Language Models." In Proceedings of the 1st Workshop on NLP for Science (NLP4Science). Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.nlp4science-1.18.

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Santana, Vinicius, Andr�s Riedemann, Pierre J. Walker, and Idelfonso Nogueira. "Langmuir.jl: An Efficient and composable Julia Package for Adsorption Thermodynamics." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.144752.

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Recent advancements in material design have made adsorption a more energy-efficient alternative to traditional thermally driven separation processes. Accurate modelling of adsorption thermodynamics is crucial for designing and operating equilibrium-limited adsorption systems. High-quality open-source packages like PyIAST, PyGAPsare available for processing adsorption data in Python. They provide a robust set of features for processing and analysing isotherms. However, they have no support for automatic differentiation and are not targeted for performance. Langmuir.jl addresses these limitation
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Weirich, Stephanie. "Session details: Automated theorem proving." In ICFP'12: ACM SIGPLAN International Conference on Functional Programming. ACM, 2012. http://dx.doi.org/10.1145/3249893.

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Paulson, Lawrence C. "Automated theorem proving for special functions." In the 2014 Symposium. ACM Press, 2014. http://dx.doi.org/10.1145/2631948.2631950.

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Wei, Yuang. "Applying Autoencoder to Automated Theorem Proving." In 2022 4th International Conference on Frontiers Technology of Information and Computer (ICFTIC). IEEE, 2022. http://dx.doi.org/10.1109/icftic57696.2022.10075262.

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Chou, Shang-Ching, Xiao-Shan Gao, and Jing-Zhong Zhang. "Automated geometry theorem proving by vector calculation." In the 1993 international symposium. ACM Press, 1993. http://dx.doi.org/10.1145/164081.164142.

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Kutzler, B., and S. Stifter. "Automated geometry theorem proving using Buchberger's algorithm." In the fifth ACM symposium. ACM Press, 1986. http://dx.doi.org/10.1145/32439.32480.

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Loveland, D. W. "Automated theorem proving: mapping logic into AI." In the ACM SIGART international symposium. ACM Press, 1986. http://dx.doi.org/10.1145/12808.12833.

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Otten, Jens. "nanoCoP: Natural Non-clausal Theorem Proving." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/695.

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Most efficient fully automated theorem provers implement proof search calculi that require the input formula to be in a clausal form, i.e. disjunctive or conjunctive normal form. The translation into clausal form introduces a significant overhead to the proof search and modifies the structure of the original formula. Translating a proof in clausal form back into a more readable non-clausal proof of the original formula is not straightforward. This paper presents a non-clausal automated theorem prover for classical first-order logic. It is based on a non-clausal connection calculus and implemen
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Adams, A. A., H. Gottliebsen, S. A. Linton, and U. Martin. "Automated theorem proving in support of computer algebra." In the 1999 international symposium. ACM Press, 1999. http://dx.doi.org/10.1145/309831.309949.

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Reports on the topic "Automated theorem proving"

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McCune, W. A case study in automated theorem proving: A difficult problem about commutators. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/27057.

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Wos, L., and W. McCune. Searching for fixed point combinators by using automated theorem proving: A preliminary report. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/6852789.

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Bellin, Gianluigi, and Jussi Ketonen. Experiments in Automatic Theorem Proving. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada327449.

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Burstein, Jill, Geoffrey LaFlair, Antony Kunnan, and Alina von Davier. A Theoretical Assessment Ecosystem for a Digital-First Assessment - The Duolingo English Test. Duolingo, 2022. http://dx.doi.org/10.46999/kiqf4328.

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The Duolingo English Test is a groundbreaking, digital­first, computer­adaptive measure of English language proficiency for communication and use in English­medium settings. The test measures four key English language proficiency constructs: Speaking, Writing, Reading, and Listening (SWRL), and is aligned with the Common European Framework of Reference for Languages (CEFR) proficiency levels and descriptors. As a digital­first assessment, the test uses “human­in­the­loop AI” from end to end for test security, automated item generation, and scoring of test­taker responses. This paper presents a
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