4 papers
A Continuous-Time and State-Space Relaxation of the Linear Threshold Model with Nonlinear Opinion Dynamics
Ian Xul Belaustegui, Himani Sinhmar, Ling-Wei Kong +2
The Linear Threshold Model (LTM) is widely used to study the propagation of collective behaviors as complex contagions. However, its dependence on discrete states and timesteps res…
Sparse dynamic network reconstruction through L1-regularization of a Lyapunov equation
Ian Xul Belaustegui, Marcela Ordorica Arango, Román Rossi-Pool +2
An important problem in many areas of science is that of recovering interaction networks from simultaneous time-series of many interacting dynamical processes. A common approach is…
Tunable Thresholds and Frequency Encoding in a Spiking NOD Controller
Ian Xul Belaustegui, Alessio Franci, Naomi Ehrich Leonard
Spiking Nonlinear Opinion Dynamics (S-NOD) is an excitable decision-making model inspired by the spiking dynamics of neurons. S-NOD enables the design of agile decision-making that…
Spiking Nonlinear Opinion Dynamics (S-NOD) for Agile Decision-Making
Charlotte Cathcart, Ian Xul Belaustegui, Alessio Franci +1
We present, analyze, and illustrate a first-of-its-kind model of two-dimensional excitable (spiking) dynamics for decision-making over two options. The model, Spiking Nonlinear Opi…