HOSS(-5): Human Organizations Simulations Start (0.1.0)
HOSS(-5) is an exploratory agent-based prototype of a small artificial society, written in Python. Each agent is a “ph” (punto humano, “human point”) that is born, is educated, works, consumes and dies. Its yearly decisions depend on a psychological profile (archetype × character), its economic status and its intentionality. Agents interact indirectly through families, firms in 10 sectors, a labour market with about 200 job categories, and a State that provides public services, employment and a Universal Basic Income, adjusting taxes and UBI each year to seek fiscal balance.
The model simulates a few thousand agents over decades of virtual time and records yearly aggregates (population, GDP, income, Gini index, HDI). A separate analysis script explores the results and fits Gamma distributions to individual incomes, comparing the shape parameter with Gini and HDI.
HOSS does not aim to predict real societies or claim empirical validation. It is a sandbox for comparing scenarios and thinking about the organizational design of society from an engineering perspective. Known limitations: no direct social relations between agents, prices and production follow simple rules rather than supply-demand dynamics, and organizations are black boxes.
The author does not plan to develop further versions. The code is released under the MIT license as an open seed for anyone who wishes to continue, criticize or transform it. Background and related work: https://onuglobal.com/de-una-tesis-a-4-piezas-de-trabajo/
Release Notes
First public release of HOSS(-5). In-memory data structures replace the MySQL backend of earlier versions; scenario parameters are set from a Tkinter GUI; results are exported to CSV and XLSX. Single-process version, chosen for data consistency.
Associated Publications
HOSS(-5): Human Organizations Simulations Start 0.1.0
HOSS(-5) is an exploratory agent-based prototype of a small artificial society, written in Python. Each agent is a “ph” (punto humano, “human point”) that is born, is educated, works, consumes and dies. Its yearly decisions depend on a psychological profile (archetype × character), its economic status and its intentionality. Agents interact indirectly through families, firms in 10 sectors, a labour market with about 200 job categories, and a State that provides public services, employment and a Universal Basic Income, adjusting taxes and UBI each year to seek fiscal balance.
The model simulates a few thousand agents over decades of virtual time and records yearly aggregates (population, GDP, income, Gini index, HDI). A separate analysis script explores the results and fits Gamma distributions to individual incomes, comparing the shape parameter with Gini and HDI.
HOSS does not aim to predict real societies or claim empirical validation. It is a sandbox for comparing scenarios and thinking about the organizational design of society from an engineering perspective. Known limitations: no direct social relations between agents, prices and production follow simple rules rather than supply-demand dynamics, and organizations are black boxes.
The author does not plan to develop further versions. The code is released under the MIT license as an open seed for anyone who wishes to continue, criticize or transform it. Background and related work: https://onuglobal.com/de-una-tesis-a-4-piezas-de-trabajo/
Release Notes
First public release of HOSS(-5). In-memory data structures replace the MySQL backend of earlier versions; scenario parameters are set from a Tkinter GUI; results are exported to CSV and XLSX. Single-process version, chosen for data consistency.