Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems
Optimization and Control
2021-11-25 v1 Systems and Control
Systems and Control
Adaptation and Self-Organizing Systems
Abstract
Given a complex system with a given interface to the rest of the world, what does it mean for a the system to behave close to a simpler specification describing the behavior at the interface? We give several definitions for useful notions of distances between a complex system and a specification by combining a behavioral and probabilistic perspective. These distances can be used to tune a complex system to a specification. We show that our approach can successfully tune non-linear networked systems to behave like much smaller networks, allowing us to aggregate large sub-networks into one or two effective nodes. Finally, we discuss similarities and differences between our approach and model reduction.
Cite
@article{arxiv.2111.12521,
title = {Probabilistic Behavioral Distance and Tuning - Reducing and aggregating complex systems},
author = {Frank Hellmann and Ekaterina Zolotarevskaia and Jürgen Kurths and Jörg Raisch},
journal= {arXiv preprint arXiv:2111.12521},
year = {2021}
}