International audienceThis paper is about a new model of opinion dynamics with opinion-dependent connectivity. We assume that agents update their opinions asynchronously and that each agent's new opinion depends on the opinions of the k agents that are closest to it. We show that the resulting dynamics is substantially different from comparable models in the literature, such as bounded-confidence models. We study the equilibria of the dynamics, observing that they are robust to perturbations caused by the introduction of new agents. We also prove that if the number of agents n is smaller than 2k, the dynamics converge to consensus. This condition is only sufficient
We study a simple continuous-time multi-agent system related to Krause’s model of opinion dynamics: ...
The paper resolves a long-standing open question in network dynamics. Averaging-based consensus has ...
The agent-based bounded confidence model of opinion dynamics of Hegselmann and Krause (2002) is refo...
International audienceThis paper is about a new model of opinion dynamics with opinion-dependent con...
This letter introduces a general model of opinion dynamics with opinion-dependent connectivity. Agen...
International audienceThis paper introduces a general model of opinion dynamics with opinion-depende...
This work explores models of opinion dynamics with opinion-dependent connectivity. Our starting poin...
This letter introduces a general model of opinion dynamics with opinion-dependent connectivity. Agen...
By using the recently introduced framework of unilateral agents interactions, we provide tight graph...
The opinion dynamics model introduced by Deffuant and Weisbuch as well as the one by Hegselmann and ...
International audienceWe study opinion dynamics in multi-agent networks where agents hold binary opi...
We study a model of opinion dynamics introduced by Krause: each agent has an opinion represented by ...
Understanding how new opinions spread through a community or how consensus emerges in noisy environm...
Individuals who interact with each other in social networks often exchange ideas and influence each ...
International audienceWe investigate opinion dynamics in multi-agent networks when a bias toward one...
We study a simple continuous-time multi-agent system related to Krause’s model of opinion dynamics: ...
The paper resolves a long-standing open question in network dynamics. Averaging-based consensus has ...
The agent-based bounded confidence model of opinion dynamics of Hegselmann and Krause (2002) is refo...
International audienceThis paper is about a new model of opinion dynamics with opinion-dependent con...
This letter introduces a general model of opinion dynamics with opinion-dependent connectivity. Agen...
International audienceThis paper introduces a general model of opinion dynamics with opinion-depende...
This work explores models of opinion dynamics with opinion-dependent connectivity. Our starting poin...
This letter introduces a general model of opinion dynamics with opinion-dependent connectivity. Agen...
By using the recently introduced framework of unilateral agents interactions, we provide tight graph...
The opinion dynamics model introduced by Deffuant and Weisbuch as well as the one by Hegselmann and ...
International audienceWe study opinion dynamics in multi-agent networks where agents hold binary opi...
We study a model of opinion dynamics introduced by Krause: each agent has an opinion represented by ...
Understanding how new opinions spread through a community or how consensus emerges in noisy environm...
Individuals who interact with each other in social networks often exchange ideas and influence each ...
International audienceWe investigate opinion dynamics in multi-agent networks when a bias toward one...
We study a simple continuous-time multi-agent system related to Krause’s model of opinion dynamics: ...
The paper resolves a long-standing open question in network dynamics. Averaging-based consensus has ...
The agent-based bounded confidence model of opinion dynamics of Hegselmann and Krause (2002) is refo...