TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhys.16.4.104
TI  - Discounted Mean-Field Game model of a dense static crowd with variable information crossed by an intruder
PY  - 2024/04/12
UR  - https://www.scipost.org/SciPostPhys.16.4.104
JF  - SciPost Physics
JA  - SciPost Phys.
VL  - 16
IS  - 4
SP  - 104
A1  - Butano, Matteo
AU  - Appert-Rolland, Cécile
AU  - Ullmo, Denis
AB  - It was demonstrated in [Bonnemain et al., Phys. Rev. E 107, 024612 (2023)] that the anticipation pattern displayed by a dense crowd crossed by an intruder can be successfully described by a minimal Mean-Field Games model. However, experiments show that changes in the pedestrian knowledge significantly modify the dynamics of the crowd. Here, we show that the addition of a single parameter, the discount factor $\gamma$, which gives a lower weight to events distant in time, is sufficient to observe the whole variety of behaviors observed in the experiments. We present a comparison between the discounted MFG and the experimental data, also providing new analytic results and insight about how the introduction of $\gamma$ modifies the model.
ER  -

@Article{10.21468/SciPostPhys.16.4.104,
	title={{Discounted Mean-Field Game model of a dense static crowd with variable information crossed by an intruder}},
	author={Matteo Butano and Cécile Appert-Rolland and Denis Ullmo},
	journal={SciPost Phys.},
	volume={16},
	pages={104},
	year={2024},
	publisher={SciPost},
	doi={10.21468/SciPostPhys.16.4.104},
	url={https://scipost.org/10.21468/SciPostPhys.16.4.104},
}