Ebook: A Journey from Process Algebra via Timed Automata to Model Learning: Essays Dedicated to Frits Vaandrager on the Occasion of His 60th Birthday
- Genre: Computers
- Series: Lecture Notes in Computer Science 13560
- Year: 2022
- Publisher: Springer
- City: Cham
- Language: English
- pdf
Non-Finite Axiomatisability Results via Reductions: CSP Parallel Composition and CCS Restriction.- Operational Causality.- Necessarily Sufficient and Sufficiently Necessary.- Axiomatizing consciousness, with applications.- Symmetric Transrationals: The Data Type and the Algorithmic Degree of its Equational Theory.- A Survey of Model Learning Techniques for Recurrent Neural Networks.- Back-and-Forth in Space: On Logics and Bisimilarity in Closure Spaces.- Better Automata through Process Algebra.- Family-Based Fingerprint Analysis: A Position Paper.- What's in School? - Topic Maps for Secondary School Computer Science.- Tree-Based Adaptive Model Learning.- From Languages to Behaviors and Back.- The Quest for an Adequate Semantic Basis of Dense-Time Metric Temporal Logic.- Equivalence Checking 40 Years After: A Review of Bisimulation Tools.- Apartness and Distinguishing formulas in Using the parallel ATerm library for parallel model checking and state space generation.- Active Automata Learning as Black-Box Search and Lazy Partition Refinement.- A Reconstruction of Ewens' Sampling Formula via Lists of Coins.- Rooted divergence-preserving branching bisimilarity is a congruence: a simpler proof.- Learning Language Intersections.- Runtime verification of compound components with ComMA.- A Basic Compositional Model for Spiking Neural Networks.- State Identification and Verification with Satisfaction.- A Note on the Message Complexity of Cidon's Distributed Depth-First Search Algorithm.- Minesweeper is difficult indeed!- Goodbye ioco.- Process Algebras and Flocks of Birds.- The Integration of Testing and Program Verification.- Discovering Directly-Follows Complete Petri Nets From Event Data.- Fair Must Testing for I/O Automata.- Passive automata learning: DFAs and NFAs.
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