The Hegselmann-Krause (HK) model belongs to the class of bounded confidence opinion dynamics. The concepts of iterative averaging and homophily that characterize the HK model can be used for the design of synchronization strategies in multi-agent systems. In this paper, the application of this technique for the synchronization of an electronic circuit is proposed. The experimental setup consists of electronic integrators, representing the agents of the model, which interact through a microcontroller that implements the iterative averaging process. Similarly to the agents in the HK model, two integrators interact if the difference between their output voltages, i.e., the agents' opinions, does not exceed a constant confidence bound. Experimental results show transient and steady-state behaviors of the system and sensitivity to confidence thresholds, by also discussing on the robustness of corresponding numerical solutions. Experiments confirm the typical phenomenon of decreasing in the number of clusters and convergence time by increasing the confidence thresholds.
An experimental verification for Hegselmann-Krause opinion dynamics
Srivastava T.
Membro del Collaboration Group
;Bernardo C.Membro del Collaboration Group
;Baccari S.Membro del Collaboration Group
;Vasca F.Membro del Collaboration Group
2023-01-01
Abstract
The Hegselmann-Krause (HK) model belongs to the class of bounded confidence opinion dynamics. The concepts of iterative averaging and homophily that characterize the HK model can be used for the design of synchronization strategies in multi-agent systems. In this paper, the application of this technique for the synchronization of an electronic circuit is proposed. The experimental setup consists of electronic integrators, representing the agents of the model, which interact through a microcontroller that implements the iterative averaging process. Similarly to the agents in the HK model, two integrators interact if the difference between their output voltages, i.e., the agents' opinions, does not exceed a constant confidence bound. Experimental results show transient and steady-state behaviors of the system and sensitivity to confidence thresholds, by also discussing on the robustness of corresponding numerical solutions. Experiments confirm the typical phenomenon of decreasing in the number of clusters and convergence time by increasing the confidence thresholds.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
