Computational Model Library


Bastien Richard Bruno Bonté Olivier Barreteau Isabelle Braud Bastien RICHARD | Published Fri Dec 20 13:44:16 2019 | Last modified Wed Oct 28 12:28:00 2020

WatASit is an agent-based model implemented in the CORMAS plateform. The model is developped to simulate irrigation situations at the operational level during a collective irrigation campaign.

Peer reviewed Multilevel Group Selection I

Garry Sotnik Thaddeus Shannon Wayne W. Wakeland | Published Tue Apr 21 18:07:27 2020 | Last modified Sat Sep 26 01:41:46 2020

The Multilevel Group Selection I (MGS I) model simulates a population of contributing and non-contributing agents, competing on a social landscape for higher-value spots in an effort to withstand some selection pressure. It may be useful to both scientists and students in hypothesis testing, theory development, or more generally in understanding multilevel group selection.

This repository contains: (1) a model calibration procedure that identifies a set of diverse, plausible models; and (2) an ABM of smallholder agriculture, which is used as a case study application for the calibration method. By identifying a set of diverse models, the calibration method attends to the issue of “equifinality” prevalent in complex systems, which is a situation where multiple plausible process descriptions exist for a single outcome.

Peer reviewed Vigilant sharing in a small-scale society

MARCOS PINHEIRO | Published Wed Jul 22 01:40:09 2020 | Last modified Wed Jul 29 02:03:28 2020

The model explores food distribution patterns that emerge in a small-scale non-agricultural group when sharing individuals engage in intentional consumption leveling with a given probability.


Deniz Kayar | Published Wed Aug 12 08:34:31 2020

This repository the multi-agent simulation software for the paper “Comparison of Competing Market Mechanisms with Reinforcement Learning in a CarPooling Scenario”. It’s a mutlithreaded Javaapplication.

Schelling and Sakoda prominently proposed computational models suggesting that strong ethnic residential segregation can be the unintended outcome of a self-reinforcing dynamic driven by choices of individuals with rather tolerant ethnic preferences. There are only few attempts to apply this view to school choice, another important arena in which ethnic segregation occurs. In the current paper, we explore with an agent-based theoretical model similar to those proposed for residential segregation, how ethnic tolerance among parents can affect the level of school segregation. More specifically, we ask whether and under which conditions school segregation could be reduced if more parents hold tolerant ethnic preferences. We move beyond earlier models of school segregation in three ways. First, we model individual school choices using a random utility discrete choice approach. Second, we vary the pattern of ethnic segregation in the residential context of school choices systematically, comparing residential maps in which segregation is unrelated to parents’ level of tolerance to residential maps reflecting their ethnic preferences. Third, we introduce heterogeneity in tolerance levels among parents belonging to the same group. Our simulation experiments suggest that ethnic school segregation can be a very robust phenomenon, occurring even when about half of the population prefers mixed to segregated schools. However, we also identify a “sweet spot” in the parameter space in which a larger proportion of tolerant parents makes the biggest difference. This is the case when parents have moderate preferences for nearby schools and there is only little residential segregation. Further experiments are presented that unravel the underlying mechanisms.

Bicycle model

Dana Kaziyeva Gudrun Wallentin Martin Loidl | Published Thu Jan 10 21:30:34 2019 | Last modified Tue Jan 15 09:39:40 2019

The purpose of the model is to generate the spatio-temporal distribution of bicycle traffic flows at a regional scale level. Disaggregated results are computed for each network segment with the minute time step. The human decision-making is governed by probabilistic rules derived from the mobility survey.

Peer reviewed BAM: The Bottom-up Adaptive Macroeconomics Model

Alejandro Platas López | Published Tue Jan 14 17:04:32 2020 | Last modified Sun Jul 26 00:26:21 2020



Modeling an economy with stable macro signals, that works as a benchmark for studying the effects of the agent activities, e.g. extortion, at the service of the elaboration of public policies..

The fight against poverty is an urgent global challenge. Microinsurance is promoted as a valuable instrument for buffering income losses due to health or climate-related risks of low-income households in developing countries. However, apart from direct positive effects they can have unintended side effects when insured households lower their contribution to traditional arrangements where risk is shared through private monetary support.

RiskNetABM is an agent-based model that captures dynamics between income losses, insurance payments and informal risk-sharing. The model explicitly includes decisions about informal transfers. It can be used to assess the impact of insurance products and informal risk-sharing arrangements on the resilience of smallholders. Specifically, it allows to analyze whether and how economic needs (i.e. level of living costs) and characteristics of extreme events (i.e. frequency, intensity and type of shock) influence the ability of insurance and informal risk-sharing to buffer income shocks. Two types of behavior with regard to private monetary transfers are explicitly distinguished: (1) all households provide transfers whenever they can afford it and (2) insured households do not show solidarity with their uninsured peers.

The model is stylized and is not used to analyze a particular case study, but represents conditions from several regions with different risk contexts where informal risk-sharing networks between smallholder farmers are prevalent.

A discrete-time stochastic model with state-dependent transmission probabilities and multi-agent simulations focusing on possible risks that could materialize in the final phase of the epidemic.

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