Aesop: White-Box Best-First Proof Search for Lean-Reference-Cited by-同舟云学术

Aesop: White-Box Best-First Proof Search for Lean

Published:2023-01-11 Issue: Volume: Page:
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Container-title:Proceedings of the 12th ACM SIGPLAN International Conference on Certified Programs and Proofs
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Author:

Limperg Jannis¹,From Asta Halkjær²

Affiliation:

1. Vrije Universiteit Amsterdam, Netherlands

2. DTU, Denmark

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3573105.3575671

Reference25 articles.

1. The Matita Interactive Theorem Prover

2. Kshitij Bansal , Sarah Loos , Markus Rabe , Christian Szegedy , and Stewart Wilcox . 2019 . HOList: an environment for machine learning of higher order logic theorem proving . In ICML 2019. 454–463. https://proceedings.mlr.press/v97/bansal19a.html Kshitij Bansal, Sarah Loos, Markus Rabe, Christian Szegedy, and Stewart Wilcox. 2019. HOList: an environment for machine learning of higher order logic theorem proving. In ICML 2019. 454–463. https://proceedings.mlr.press/v97/bansal19a.html

3. The lean mathematical library

4. Judy Crow , Sam Owre , John Rushby , Natarajan Shankar , and Mandayam Srivas . 1995 . A Tutorial Introduction to PVS . In Workshop on Industrial-Strength Formal Specification Techniques 1995. http://www.csl.sri.com/papers/wift-tutorial/ Judy Crow, Sam Owre, John Rushby, Natarajan Shankar, and Mandayam Srivas. 1995. A Tutorial Introduction to PVS. In Workshop on Industrial-Strength Formal Specification Techniques 1995. http://www.csl.sri.com/papers/wift-tutorial/

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