Error-driven Global Transition in a Competitive Population on a Network
Sehyo Charley Choe, Neil F. Johnson, Pak Ming Hui
Abstract
We show, both analytically and numerically, that erroneous data transmission generates a global transition within a competitive population playing the Minority Game on a network. This transition, which resembles a phase transition, is driven by a `temporal symmetry breaking' in the global outcome series. The phase boundary, which is a function of the network connectivity p and the error probability q, is described quantitatively by the Crowd-Anticrowd theory.
Create a lesson
Related papers
Cell-type-specific modularity in E/I networks shapes dynamical regimes and computational capabilities
Emmanouil Giannakakis, Victor Buendía, Oleg Vinogradov et al.
Finite-width shift of the edge of chaos in deep neural networks
Arn Caesar
Neural Networks with Exciton-Polariton Waveguides
Huawen Xu, Ruiqi Bao, Lingyu Tian et al.
Optical Ceiling on Polaron Mobility in Disordered Molecular Semiconductors: Lessons from Eumelanin
Alvan Hunt
Glauber dynamics of the Sherrington--Kirkpatrick spin-glass model: a dynamical cavity method
Grzegorz Szamel
Generative diffusion in long-range correlated landscapes: Speciation cascade and the foam structure of the score
Jerome Garnier-Brun, Giulio Biroli, Marc Mézard et al.