Statistical mechanics of competitive resource allocation using agent-based models

Authored by Matteo Marsili, Damien Challet, Anirban Chakraborti, Arnab Chatterjee, Yi-Cheng Zhang, Bikas K Chakrabarti

Date Published: 2015

DOI: 10.1016/j.physrep.2014.09.006

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

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 (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) 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 of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines. (C) 2014 Elsevier B.V. All rights reserved.

Tags

Evolutionary game Heterogeneous agents Interacting neural-networks Generating functional-analysis Genetic crossover strategies Spherical minority game Stable marriage problem Adaptive competition Socioeconomic systems Recommender systems