Computational Model Library

PolicySpace models public policies within an empirical, spatial environment using data from 46 metropolitan regions in Brazil. The model contains citizens, markets, residences, municipalities, commuting and a the tax scheme. In the associated publications (book in press and https://arxiv.org/abs/1801.00259) we validate the model and demonstrate an application of the fiscal analysis. Besides providing the basics of the platform, our results indicate the relevance of the rules of taxes transfer for cities’ quality of life.

Machine Learning simulates Agent-based Model

B Furtado | Published Wed Mar 7 13:10:49 2018

This is an initial exploratory exercise done for the class @ http://thiagomarzagao.com/teaching/ipea/ Text available here: https://arxiv.org/abs/1712.04429v1
The program:
Reads output from an ABM model and its parameters’ configuration
Creates a socioeconomic optimal output based on two ABM results of the modelers choice
Organizes the data as X and Y matrices
Trains some Machine Learning algorithms

Extended Flache and Mas (2008)

Hadi Aliahmadi | Published Wed Aug 16 22:32:04 2017 | Last modified Mon Feb 26 20:03:46 2018

We extend the Flache-Mäs model to incorporate the location and dyadic communication regime of the agents in the opinion formation process. We make spatially proximate agents more likely to interact with each other in a pairwise communication regime.

A simple agent-based spatial model of the economy

Bernardo Alves Furtado Isaque Daniel Rocha Eberhardt | Published Thu Mar 10 18:26:16 2016 | Last modified Tue Nov 22 15:08:38 2016

The modeling includes citizens, bounded into families; firms and governments; all of them interacting in markets for goods, labor and real estate. The model is spatial and dynamic.

This is an adaptation and extension of Robert Axtell’s model (2013) of endogenous firms, in Python 3.4

Land Use in the Chitwan Valley

Alex Zvoleff | Published Mon Jun 2 01:42:22 2014

chitwanabm is a spatially explicit agent-based model of population and land use in the Chitwan Valley, Nepal, designed to explore feedbacks between population and environment, with a heavy focus on community context and individual-level variation.

ergodicity_test

Jakob Grazzini | Published Mon Nov 29 19:22:53 2010 | Last modified Sat Apr 27 20:18:30 2013

This Python module contain a function that is able to test the ergodicity of a given agent based model. It is sufficient to produce one long time series and many smaller time series. The function uses

Stationarity Test

Jakob Grazzini | Published Mon Nov 29 19:26:39 2010 | Last modified Sat Apr 27 20:18:48 2013

This is a stationarity test, it tests whether a given moment is constant during the time series (null hypothesis). The Wald Wolfowitz nonparametric fitness test is applied to time series.

This generic model simulates climate change adaptation in the form of resistance, accommodation, and retreat in coastal regions vulnerable to sea level rise and flooding. It tracks how population changes as households retreat to higher ground.

We present an Agent-Based Stock Flow Consistent Multi-Country model of a Currency Union to analyze the impact of changes in the fiscal regimes that is permanent changes in the deficit-to-GDP targets that governments commit to comply.

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