The workings of the Maximum Entropy Principle in collective human behavior

Abstract

We exhibit compelling evidence regarding how well does the MaxEnt principle describe the rank-distribution of city-populations via an exhaustive study of the 50 Spanish provinces (more than 8000 cities) in a time-window of 15 years (1996-2010). We show that the dynamics that governs the population-growth is the deciding factor that originates the observed distributions. The connection between dynamics and distributions is unravelled via MaxEnt.

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• Statistical physics of social dynamics
• Scaling and universality in proportional elections
• Generalized entropies and the transformation group of superstatistics
• Zipf's law unzipped
• MaxEnt and dynamical information
• Tsallis' deformation parameter q quantifies the classical-quantum transition

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• Stationary Stability for Evolutionary Dynamics in Finite Populations
• Memory endowed US cities and their demographic interactions
• Comment on "Black Hole Entropy: A Closer Look"
• A maximum entropy network reconstruction of macroeconomic models
• Maximum Entropy Principle Analysis in Network Systems with Short-time Recordings
• A Unified View of Transport Equations
• Family of Probability Distributions Derived from Maximal Entropy Principle with Scale Invariant Restrictions
• Incentive Processes in Finite Populations
• Planning and Learning Using Adaptive Entropy Tree Search
• Space-time correlations in urban population flows