Statistical mechanics of competitive resource allocation using agent-based models - Archive ouverte HAL Access content directly
Journal Articles Physics Reports Year : 2015

Statistical mechanics of competitive resource allocation using agent-based models

Abstract

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.
Fichier principal
Vignette du fichier
challet_statistical_mechanics.pdf (731.39 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00834380 , version 1 (21-04-2020)

Identifiers

Cite

Anirban Chakraborti, Damien Challet, Arnab Chatterjee, Matteo Marsili, Yi-Cheng Zhang, et al.. Statistical mechanics of competitive resource allocation using agent-based models. Physics Reports, 2015, 552, pp.1-25. ⟨10.1016/j.physrep.2014.09.006⟩. ⟨hal-00834380⟩
225 View
79 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More