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Formal Modeling and Analysis of Timed Systems: 20th International Conference, FORMATS 2022, Warsaw, Poland, September 1315, 2022, Proceedings 1st ed. 2022 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 307 pages, height x width: 235x155 mm, weight: 498 g, 34 Illustrations, color; 26 Illustrations, black and white; XVII, 307 p. 60 illus., 34 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 13465
  • Izdošanas datums: 29-Aug-2022
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031158385
  • ISBN-13: 9783031158384
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  • Mīkstie vāki
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Formal Modeling and Analysis of Timed Systems: 20th International Conference, FORMATS 2022, Warsaw, Poland, September 1315, 2022, Proceedings 1st ed. 2022Palielināt
  • Formāts: Paperback / softback, 307 pages, height x width: 235x155 mm, weight: 498 g, 34 Illustrations, color; 26 Illustrations, black and white; XVII, 307 p. 60 illus., 34 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 13465
  • Izdošanas datums: 29-Aug-2022
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031158385
  • ISBN-13: 9783031158384
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031158384.html
Keywords:
This book constitutes the refereed proceedings of the 20th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2022, held in Warsaw, Poland, in September 2022. The 12 full papers together with 2 short papers that were carefully reviewed and selected from 30 submissions are presented in this volume with 3 full-length papers associated with invited/anniversary talks. The papers focus on topics such as modelling, design and analysis of timed computational systems. The conference aims in real-time issues in hardware design, performance analysis, real-time software, scheduling, semantics and verification of real-timed, hybrid and probabilistic systems.
Invited Papers.- Probabilistic and Timed Systems.- Temporal Logic.- Timed Automata and Games.- Neural Networks.- Reinforcement Learning.