Metaheuristic Algorithms for Proof Searching in HOL4 Article Swipe
M. Saqib Nawaz
,
Muhammad Zohaib Nawaz
,
Osman Hasan
,
Philippe Fournier‐Viger
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.18293/seke2022-103
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.18293/seke2022-103
User guided proof development in interactive theorem proving is a manual and time consuming activity.For automating proof searching and optimization in a higher-order logic proof assistant, we provide two metaheuristic algorithms that are based on Fitness Dependent Optimizer (FDO) and Bat Algorithm (BA).In both metaheuristic algorithms, random proof sequences are first created from a population of frequently occurring proof steps that are discovered using pattern mining techniques.Created proof sequences are then evolved till their fitness matches the fitness of the original (or target) proof sequences.Experiments are performed to investigate the performance of the proposed algorithms on different HOL4 theories.Moreover, the proposed FDO and BA-based proof searching approaches are compared with Simulated Annealing (SA) and Genetic Algorithm (GA)based methods.Results show that BA performs best, followed by FDO and SA for proof finding and optimization in HOL4.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.18293/seke2022-103
- https://doi.org/10.18293/seke2022-103
- OA Status
- bronze
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4294659115
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4294659115Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.18293/seke2022-103Digital Object Identifier
- Title
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Metaheuristic Algorithms for Proof Searching in HOL4Work title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-07-01Full publication date if available
- Authors
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M. Saqib Nawaz, Muhammad Zohaib Nawaz, Osman Hasan, Philippe Fournier‐VigerList of authors in order
- Landing page
-
https://doi.org/10.18293/seke2022-103Publisher landing page
- PDF URL
-
https://doi.org/10.18293/seke2022-103Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://doi.org/10.18293/seke2022-103Direct OA link when available
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Proof of concept, Metaheuristic, Computer science, Simulated annealing, Algorithm, Automated theorem proving, Proof theory, Genetic algorithm, Theoretical computer science, Mathematics, Mathematical proof, Machine learning, Operating system, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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25Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.followed | 123 |
| abstract_inverted_index.original | 80 |
| abstract_inverted_index.performs | 121 |
| abstract_inverted_index.proposed | 93, 100 |
| abstract_inverted_index.(GA)based | 116 |
| abstract_inverted_index.Algorithm | 41, 115 |
| abstract_inverted_index.Annealing | 111 |
| abstract_inverted_index.Dependent | 36 |
| abstract_inverted_index.Optimizer | 37 |
| abstract_inverted_index.Simulated | 110 |
| abstract_inverted_index.consuming | 13 |
| abstract_inverted_index.different | 96 |
| abstract_inverted_index.occurring | 57 |
| abstract_inverted_index.performed | 86 |
| abstract_inverted_index.searching | 17, 105 |
| abstract_inverted_index.sequences | 48, 68 |
| abstract_inverted_index.algorithms | 30, 94 |
| abstract_inverted_index.approaches | 106 |
| abstract_inverted_index.assistant, | 25 |
| abstract_inverted_index.automating | 15 |
| abstract_inverted_index.discovered | 62 |
| abstract_inverted_index.frequently | 56 |
| abstract_inverted_index.population | 54 |
| abstract_inverted_index.algorithms, | 45 |
| abstract_inverted_index.development | 3 |
| abstract_inverted_index.interactive | 5 |
| abstract_inverted_index.investigate | 88 |
| abstract_inverted_index.performance | 90 |
| abstract_inverted_index.activity.For | 14 |
| abstract_inverted_index.higher-order | 22 |
| abstract_inverted_index.optimization | 19, 132 |
| abstract_inverted_index.metaheuristic | 29, 44 |
| abstract_inverted_index.methods.Results | 117 |
| abstract_inverted_index.techniques.Created | 66 |
| abstract_inverted_index.theories.Moreover, | 98 |
| abstract_inverted_index.sequences.Experiments | 84 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.1032261 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |