Consensus in the weighted voter model with noise-free and noisy observations

# 223





Abstract

Collective decision-making is an important problem in swarm robotics arising in many different contexts and applications. The Weighted Voter Model has been proposed to collectively solve the best-of-n problem, and analysed in the thermodynamic limit. We present an exact finite-population analysis of the best-of-two model on complete as well as regular network topologies. We also present a novel analysis of this model when agent evaluations of options suffer from measurement error.

Prof. Ayalvadi Ganesh, University of Bristol

Ayalvadi Ganesh is an Associate Professor at the School of Mathematics, University of Bristol. His research interests include large deviations, queueing theory, random graph dynamics, and decentralised algorithms. He won the INFORMS Best Publication Award in 2005 and the ACM Sigmetrics Best Paper Prize in 2010.