Kinetic models for topological nearest-neighbor interactions

Adrien Blanchet and Pierre Degond

No 17-786, TSE Working Papers from Toulouse School of Economics (TSE)

Abstract: We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in [10]. The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.

Keywords: rank-based interaction; spatial diffusion equation; continuity equation; concentration of measure (search for similar items in EconPapers)
Date: 2017-03
New Economics Papers: this item is included in nep-ure
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Working Paper: Kinetic models for topological nearest-neighbor interactions (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:31577

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