DeepAI AI Chat
Log In Sign Up

Modelling collective motion based on the principle of agency

by   Katja Ried, et al.

Collective motion is an intriguing phenomenon, especially considering that it arises from a set of simple rules governing local interactions between individuals. In theoretical models, these rules are normally assumed to take a particular form, possibly constrained by heuristic arguments. We propose a new class of models, which describe the individuals as agents, capable of deciding for themselves how to act and learning from their experiences. The local interaction rules do not need to be postulated in this model, since they emerge from the learning process. We apply this ansatz to a concrete scenario involving marching locusts, in order to model the phenomenon of density-dependent alignment. We show that our learning agent-based model can account for a Fokker-Planck equation that describes the collective motion and, most notably, that the agents can learn the appropriate local interactions, requiring no strong previous assumptions on their form. These results suggest that learning agent-based models are a powerful tool for studying a broader class of problems involving collective motion and animal agency in general.


page 6

page 10

page 18


Nonlocal flocking dynamics: Learning the fractional order of PDEs from particle simulations

Flocking refers to collective behavior of a large number of interacting ...

An active inference model of collective intelligence

To date, formal models of collective intelligence have lacked a plausibl...

Towards Agent-based Models of Rumours in Organizations: A Social Practice Theory Approach

Rumour is a collective emergent phenomenon with a potential for provokin...

Agent-based models of collective intelligence

Collective or group intelligence is manifested in the fact that a team o...

Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach

We present an Equation/Variable free machine learning (EVFML) framework ...

Discovering mesoscopic descriptions of collective movement with neural stochastic modelling

Collective motion is an ubiquitous phenomenon in nature, inspiring engin...