Decision Modeling in Markovian Multi-Agent Systems
Paper in proceeding, 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.

Multi-agent systems

opinion dynamics

Author

Carl-Johan Heiker

Chalmers, Electrical Engineering, Systems and control

Paolo Falcone

University of Modena and Reggio Emilia

Chalmers, Electrical Engineering, Systems and control

Proceedings of the IEEE Conference on Decision and Control

07431546 (ISSN) 25762370 (eISSN)

Vol. 2022-December 7235-7240
978-1-6654-6761-2 (ISBN)

61st IEEE Conference on Decision and Control (CDC)
Cancún, Mexico,

5G for Connected Autonomous Vehicles in Complex Urban Environments

VINNOVA (2018-05005), 2019-04-01 -- 2023-03-31.

Areas of Advance

Information and Communication Technology

Transport

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/CDC51059.2022.9993134

ISBN

9781665467612

More information

Latest update

7/17/2024