Collective Decision Making using Attractive and Repulsive Forces in Markovian Opinion Dynamics
Preprint, 2022

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.

Stochastic systems

Markov processes

Transportation networks

Agents-based systems

Author

Carl-Johan Heiker

Chalmers, Electrical Engineering, Systems and control

Paolo Falcone

Chalmers, Electrical Engineering, Systems and control

Subject Categories

Information Science

Control Engineering

More information

Latest update

12/2/2022