Abstract:

A central challenge in understanding the concept of swarm intelligence is the relation between the behavior of a swarm of agents and its ecological niche. In order to interpret such collective concept, we have been using analytical and synthetic approaches to get more insights using mainly one particular biological system of Sulphur mollies as study system. We have combined analytical behavioral characterizations of schools of these fish with synthetic state-of-the-art machine learning methods to understand the  functionality of the behavior in real life. In this talk, we will show our main findings related to the collective behavior. We will show i) that the highly synchronized diving behavior of the school is close to criticality, ii) how this can be functionally related to effective communication about predator attacks, and iii) how to study the heterogeneity in collectives by inferring the parameters of models using machine learning algorithms.

***Want to attend one of our events? Sign up here.
To get regular updates, subscribe to our mailing list from this page.
This talk will take place in person at SCIoI.