Reachability Problems 18th International Conference, RP 2024, Vienna, Austria, September 25–27, 2024, Proceedings /

This book constitutes the proceedings of the 18th International Conference on Reachability Problems, RP 2024, which took place in Vienna, Austria, during September 25–27, 2024. The 13 full papers included in these proceedings were carefully reviewed and selected from 37 submissions. The book also co...

Mô tả đầy đủ

Đã lưu trong:
Chi tiết về thư mục
Tác giả của công ty: SpringerLink (Online service)
Tác giả khác: Kovács, Laura (Biên tập viên), Sokolova, Ana (Biên tập viên)
Định dạng: Điện tử eBook
Ngôn ngữ:Tiếng Anh
Được phát hành: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Phiên bản:1st ed. 2024.
Loạt:Lecture Notes in Computer Science, 15050
Những chủ đề:
Truy cập trực tuyến:https://doi.org/10.1007/978-3-031-72621-7
Các nhãn: Thêm thẻ
Không có thẻ, Là người đầu tiên thẻ bản ghi này!
Mục lục:
  • Invited Papers
  • Quantifying Uncertainty in Probabilistic Loops without Sampling: a Fully Automated Approach.-The Satis ability and Validity Problems for Probabilistic CTL.-Computability and Reachability
  • Computing Reachable Simulations on Transition Systems
  • Computing All Minimal Ways to Reach a Context-Free Language
  • On Solving All-Path Reachability Problems for Starvation Freedom of Concurrent Rewrite Systems under Process Fairness
  • Automata and Complexity
  • Rollercoasters with Plateaus
  • Quantum Automata and Languages of Finite Index
  • On Shortest Products for Nonnegative Matrix Mortality
  • Hardness of Busy Beaver Value BB(15)
  • Linear Systems and Recurrences
  • On the Complexity of Reachability and Mortality for Bounded Piecewise Affine Maps
  • Semi-Linear VASR for Over-Approximate Semi-Linear System Reachability.-Reachability in Linear Recurrence Automata
  • Games and Abstractions
  • Robust Deterministic Abstractions for Supervising Discrete-time Continuous Systems
  • Markov Decision Processes with Sure Parity and Multiple Reachability Objectives
  • Modelling Dynamical Systems: Learning ODEs with No Internal ODE Resolution.