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  Scarlet: Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logic

Raha, R., Roy, R., Fijalkow, N., & Neider, D. (2024). Scarlet: Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logic. The Journal of Open Source Software, 9(93): 5052, pp. 1-4. doi:10.21105/joss.05052.

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Genre: Journal Article
Latex : Scarlet: {S}calable Anytime Algorithms for Learning Fragments of Linear Temporal Logic

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10.21105.joss.05052.pdf (Publisher version), 209KB
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 Creators:
Raha, Ritam1, Author
Roy, Rajarshi2, Author           
Fijalkow, Nathanaël1, Author
Neider, Daniel1, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Group R. Majumdar, Max Planck Institute for Software Systems, Max Planck Society, ou_2105292              

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Language(s): enc - En
 Dates: 20242024
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: BibTex Citekey: Raha23
DOI: 10.21105/joss.05052
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Title: The Journal of Open Source Software
  Abbreviation : J. Open Source Softw.
  Abbreviation : JOSS
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 9 (93) Sequence Number: 5052 Start / End Page: 1 - 4 Identifier: ISSN: 2475-9066
CoNE: https://pure.mpg.de/cone/journals/resource/2475-9066