The $s$-Energy and Its Applications
Chazelle, Bernard, Karntikoon, Kritkorn
–arXiv.org Artificial Intelligence
Averaging dynamics drives countless processes in physics, biology, engineering, and the social sciences. In recent years, the $s$-energy has emerged as a useful tool for bounding the convergence rates of time-varying averaging systems. We derive new bounds on the $s$-energy, which we use to resolve a number of open questions in the areas of bird flocking, opinion dynamics, and distributed motion coordination. We also use our results to provide a theoretical validation for the idea of the "Overton Window" as an attracting manifold of viable group opinions. Our new bounds on the $s$-energy highlight its dependency on the connectivity of the underlying networks. In this vein, we use the $s$-energy to explain the exponential gap in the convergence rates of stationary and time-varying consensus systems.
arXiv.org Artificial Intelligence
Oct-12-2024
- Country:
- North America
- United States
- Massachusetts (0.04)
- Rhode Island > Providence County
- Providence (0.04)
- Mexico > Quintana Roo
- Cancún (0.04)
- United States
- Europe
- Italy (0.04)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.04)
- Spain > Andalusia
- Seville Province > Seville (0.04)
- Asia > Japan
- Honshū > Kansai > Kyoto Prefecture > Kyoto (0.04)
- North America
- Genre:
- Research Report > New Finding (0.34)
- Industry:
- Government (0.67)
- Health & Medicine (0.46)
- Technology: