Buch, Englisch, 163 Seiten, Format (B × H): 155 mm x 235 mm
13th International Symposium, DataMod 2025, Toledo, Spain, November 10-11, 2025, Revised Selected Papers
Buch, Englisch, 163 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-032-25551-8
Verlag: Springer Nature Switzerland AG
This book constitutes revised selected papers of the 13th International Symposium on From Data Models and Back, DataMod 2025, held in Toledo, Spain, during November 10–11, 2025.
The 7 full papers and 1 sort paper included in this book were carefully reviewed and selected from 12 submissions. These papers present research results in the floowing areas:
Modelling methodologies of interest include automata, agents, Petri nets, process algebras and rewriting systems.
Application domains include social systems, ecology, biology, medicine, smart cities, governance, security, education, software engineering, and any other field that deals with complex systems and large amounts of data.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Technische Informatik
Weitere Infos & Material
.- Explainable Root Cause Analysis for Microservices’ Incomplete Logs.
.- Efficient Construction of Reachability Graphs for Petri Net Product Lines.
.- Probabilistic Algorithm with Dynamic Load Balancing for GPU-Accelerated Tumor Growth Simulations.
.- Reachability Specification Adaptation for Continuous Dynamical Systems.
.- Ruleless Digital Twins.
.- Physics-Informed Neural Networks for SIR Models: Evaluating Data Integration Strategies.
.- Low-Cost Embedded PSO for Decentralized, Scalable and Sustainable Hydroelectric Dispatch.
.- On the Relationship Between Neural Gradients and Model Reasoning.
.- Taylor’s DAgger: Verified Integration for Efficient Imitation Learning of an MPC*.
.- From Transformers to Weighted Automata: Towards the Verification of Large Language Models.
