Project Description

Societies rely on finite resources and environments prone to systemic fluctuations, shocks, and crises. These dynamics heighten uncertainty and complicate decision-making in urban management and planning. A classic concept from information theory—entropy, a measure of uncertainty and disorder—helps clarify the nature of these challenges. Societies constantly face entropy. Preparing for its negative effects, such as instability and crises, is essential for building resilience. Equally crucial, however, is fostering positive entropic effects driven by innovation and serendipity, enabling creative societies to navigate contradictions and conflicts effectively. Cities play a pivotal role in both processes. They are simultaneously composed of social actions, physical materiality, and meanings. This convergence can create contradictions, particularly in the co-evolution of rapidly changing systems, such as social interactions, and slower-changing systems, such as the built environment. Urban structures may amplify "noise" within dynamic interacting systems, leading to mismatches among a city's subsystems—social, informational, and material.

This research seeks to understand how interactions emerge alongside the built environment and to identify potential sources of noise in their co-evolution. The hypothesis posits that societies manage and reduce entropy through three continuous processes: creating urban structures to support volatile interaction systems; utilizing these structures to sustain social reproduction, and improving them in response to environmental and social fluctuations through self-organizing mechanisms like bottom-up collective learning and top-down planning and monitoring. Cities influence the functioning of societies by either mitigating or exacerbating environmental demands and externalities, serving as structures that shape and enable collective life. This study applies information theory to analyze how urban conditions facilitate the self-organization of collective life through the convergence of actions in the form of social cooperation.

The project develops computational tools, specifically Agent-Based Models (ABMs), to explore levels of cooperation as a counterforce to "social entropy" across cities in different world regions. A key innovation is a tool designed to identify "entropic urban areas" that could negatively impact social capacity for collective action. The tool also enables comparisons between current urban states and counterfactual scenarios, assessing the potential effects of hypothetical changes on social entropy. This new responsiveness and sustainability assessment tool is particularly relevant for cities experiencing rapid growth, structural vulnerabilities, and spatial inequalities in mobility and access to urban opportunities. By addressing these challenges, the research aims to enhance our understanding of how cities can foster resilient, cooperative, and adaptive societies.

Research Team

· Vinicius M. Netto

Collaborators

· Kimon Krenz, Urban data science, spatial analysis, University College London (UCL), UK.

· Diego Rybski, Statistical physics and complex systems, city science, Leibniz Institute of Ecological Urban and Regional Development (IOER), Germany.

· Fabiano L. Ribeiro Department of Physics, Federal University of Lavras (UFLA), Brazil

· Caio Cacholas, Urban modelling, Universidade Federal Fluminense (PPGAU UFF), Brazil.

Financial Support

· Conselho Nacional de Pesquisa CNPq Nº 09/2021 - 'Productivity in research’. R$ 75.600,00 (3 years)

Stage of Progress

· Ongoing (since 2021)