Difference between revisions of "Collective motions of animals"
| Line 1: | Line 1: | ||
| − | + | ||
''' Background''' :From bird flocks to fish schools, from insect flights to cell movements during embryogenesis, from pedestrian motions to robotics, collective motion is ubiquitous in many natural and artificial systems. This is a fascinating phenomenon that reflects the ability of the nature to create complexity. The main question is to determine what are the mechanisms regulating collective motion and whether those mechanisms are as complex as what we can observe in natural systems. | ''' Background''' :From bird flocks to fish schools, from insect flights to cell movements during embryogenesis, from pedestrian motions to robotics, collective motion is ubiquitous in many natural and artificial systems. This is a fascinating phenomenon that reflects the ability of the nature to create complexity. The main question is to determine what are the mechanisms regulating collective motion and whether those mechanisms are as complex as what we can observe in natural systems. | ||
| − | '''Goal''' :The goal of this project is to implement a simple model of collective behavior, run simulations and generate data. From this synthetic data we aim to investigate the properties of the motion | + | '''Goal''' :The goal of this project is to implement a simple model of collective behavior, run simulations and generate data. From this synthetic data we aim to investigate the properties of the motion, the robustness of the collective dynamics with respect to endogenous/exogenous perturbations and compare the results of the simulations with data of bacterial motion. |
| − | '''Tools''' : Stochastic modeling, equations of motion, diffusion equations, shape analysis | + | '''Tools''' : Stochastic modeling, equations of motion, diffusion equations, shape analysis. Programing with C or C++ or Python. |
Revision as of 14:18, 16 February 2017
Background :From bird flocks to fish schools, from insect flights to cell movements during embryogenesis, from pedestrian motions to robotics, collective motion is ubiquitous in many natural and artificial systems. This is a fascinating phenomenon that reflects the ability of the nature to create complexity. The main question is to determine what are the mechanisms regulating collective motion and whether those mechanisms are as complex as what we can observe in natural systems.
Goal :The goal of this project is to implement a simple model of collective behavior, run simulations and generate data. From this synthetic data we aim to investigate the properties of the motion, the robustness of the collective dynamics with respect to endogenous/exogenous perturbations and compare the results of the simulations with data of bacterial motion.
Tools : Stochastic modeling, equations of motion, diffusion equations, shape analysis. Programing with C or C++ or Python.
