Work

Maximal dispersion of adaptive random walks

Year: 2022

Type: article

Abstract: The challenge of maximizing dispersion of a dynamical process over a globally unknown network is overcome by introducing an adaptive random walk. This adaptive random walk, through a large-deviation-theory approach, updates its transition rule on the local information collected while exploring the network.

Source: Physical Review Research

DOI: 10.1103/physrevresearch.4.l042051

Authors: Gabriele Di Bona, Leonardo Di Gaetano, Vito Latora, Francesco Coghi

Institutions: Queen Mary University of London, Central European University, University of Catania, Complexity Science Hub, Nordic Institute for Theoretical Physics, Stockholm University, KTH Royal Institute of Technology

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,812

OpenAlex ID: W4313304133

FWCI: 0.373

Cites: 54

Cited by: 4

Related to: 10