Events Detail

Speaker:
Prof. Dr. Roland Bouffanais, University of Geneva

Join the talk on Zoom

For a multi-agent system to respond effectively to evolving environmental conditions, proper information exchange among its units is paramount. This information transfer can either take the form of a simple contagion—stemming from pairwise interactions—or a complex contagion—involving social influence and reinforcement.

It is worth noting that the concept of complex contagion has so far been limited to a specific class of collective decision-making process, namely nonlinear binary-option models with a threshold. The interest in threshold models can be traced to their mathematical simplicity, their paradigmatic nature, and their success in modelling the spread of behaviours in various social settings. However, many collective decision-making processes encountered in social and biological systems are devoid of any threshold or nonlinearities, and involve continuous decision variables.

In this talk, we will discuss the generalization of the concept of complex contagion to consensus-based decision-making processes. Specifically, we will present some recent results revealing that a transition from simple to complex contagion, as originally identified in threshold-based models, can also be exhibited by another general class of consensus-based decision-making processes. Using concepts borrowed from network science, we identified a new way of characterizing complex contagions, and used it to uncover their existence in consensus-based dynamics.

The results discussed in this talk have far-reaching implications. First, they extend the concept of transition from simple to complex contagion—heretofore limited to binary threshold-based models—to the continuous class of consensus-based models. Second, these results reveal that the nature of the contagion—simple or complex—is directly related to the type of behaviour spreading, and specifically to the pace of its intrinsic dynamics—e.g., slow external perturbations vs. collective startle response.

Roland Bouffanais is an Associate Professor with the Department of Computer Science (Faculty of Science) of the University of Geneva. His research on complex systems involves a synergistic combination of computational and theoretical developments with real-life experimental validations. Specifically, he focuses on interdisciplinary research at the intersection of complexity science and swarm intelligence. Over the past three years, Bouffanais investigated problems focused on social contagions and collective decision-making. Roland Bouffanais has published 110+ peer-reviewed papers in top-rated scientific journals and selective conference proceedings. He has authored a monograph titled Design and Control of Swarm Dynamics, published by Springer in their Complexity Series in 2016. Bouffanais has also published numerous Opinion Pieces and Op-Eds in various newspapers in Asia, Europe, and North America.