Collective Decision Making using Attractive and Repulsive Forces in Markovian Opinion Dynamics
Abstract
In this paper, we model a decision-making process involving a set of interacting agents. We use Markovian opinion dynamics, where each agent switches between decisions according to a continuous time Markov chain. Existing opinion dynamics models are extended by introducing attractive and repulsive forces that act within and between groups of agents, respectively. Such an extension enables the resemblance of behaviours emerging in networks where agents make decisions that depend both on their own preferences and the decisions of specific groups of surrounding agents. The considered modeling problem and the contributions in this paper are inspired by the interaction among road users (RUs) at traffic junctions, where each RU has to decide whether to go or to yield.
Keywords
Cite
@article{arxiv.2203.11116,
title = {Collective Decision Making using Attractive and Repulsive Forces in Markovian Opinion Dynamics},
author = {Carl-Johan Heiker and Paolo Falcone},
journal= {arXiv preprint arXiv:2203.11116},
year = {2022}
}
Comments
Revised version of our original submission. Major changes include a new example application throughout the paper, which consists of a Yield/Go state traffic intersection problem, a reformulation of the repulsive force function, an updated derivation of the marginalized model and a results section that considers the Yield/Go intersection problem