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Discounted Mean-Field Game model of a dense static crowd with variable information crossed by an intruder
by Matteo Butano, Cécile Appert-Rolland, Denis Ullmo
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Submission summary
| Authors (as registered SciPost users): | Matteo Butano · Denis Ullmo |
| Submission information | |
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| Preprint Link: | https://arxiv.org/abs/2302.08945v3 (pdf) |
| Code repository: | https://github.com/matteobutano/mfg_ergodic_intruder |
| Date accepted: | 2024-03-25 |
| Date submitted: | 2024-02-08 11:09 |
| Submitted by: | Butano, Matteo |
| Submitted to: | SciPost Physics |
| Ontological classification | |
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| Academic field: | Physics |
| Specialties: |
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| Approaches: | Theoretical, Computational |
Abstract
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.
Author comments upon resubmission
We have answered the referee's remarks and we have attached to the related comment, as done previously, a copy of the manuscript where the corresponding changes are highlighted in blue.
Best remarks
Matteo Butano, Cécile Appert-Rolland, Denis Ullmo
Published as SciPost Phys. 16, 104 (2024)