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  Adaptive Strategies for rLTL Games

Nayak, S. P., Neider, D., & Zimmermann., M. (2021). Adaptive Strategies for rLTL Games. In HSCC2021 (pp. 1-2). New York, NY: ACM. doi:10.1145/3447928.3457210.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-57C8-4 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-57C9-3
Genre: Conference Paper
Latex : Adaptive Strategies for {rLTL} Games

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 Creators:
Nayak, Satya Prakash1, Author
Neider, Daniel2, Author           
Zimmermann., Martin1, 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): eng - English
 Dates: 2021
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Nayak_HSCC21
DOI: 10.1145/3447928.3457210
 Degree: -

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Title: 24th International Conference on Hybrid Systems: Computation and Control
Place of Event: Neshville, TN, USA
Start-/End Date: 2021-05-19 - 2021-05-21

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Title: HSCC2021
  Subtitle : Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control (part of CPS-IoT Week)
  Abbreviation : HSCC 2021
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: New York, NY : ACM
Pages: - Volume / Issue: - Sequence Number: 32 Start / End Page: 1 - 2 Identifier: ISBN: 978-1-45038339-4