Computational Model Library

Peer reviewed MGA - Minimal Genetic Algorithm

Cosimo Leuci | Published Tue Sep 3 07:52:29 2019 | Last modified Thu Jan 30 08:42:08 2020

Genetic algorithms try to solve a computational problem following some principles of organic evolution. This model has educational purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the possible answers to solve the problem are represented by agents, that in logo programming environment are usually known as “turtles”.

Peer reviewed MigrAgent

Rocco Paolillo Wander Jager | Published Fri Oct 5 09:59:44 2018 | Last modified Wed Nov 28 14:03:41 2018

MigrAgent simulates migration flows of a population from a home country to a host country and mutual adaptation of a migrant and local population post-migration. Agents accept interactions in intercultural networks depending on their degree of conservatism. Conservatism is a group-level parameter normally distributed within each ethnic group. Individual conservatism changes as function of reciprocity of interaction in intergroup experiences of acceptance or rejection.

The aim of MigrAgent is to unfold different outcomes of integration, assimilation, separation and marginalization in terms of networks as effect of different degrees of conservatism in each group and speed of migration flows.

This model represents an agent-based social simulation for citizenship competences. In this model people interact by solving different conflicts and a conflict is solved or not considering two possible escenarios: when individual citizenship competences are considered and when not. In both cases the TKI conflict resolution styles are considered. Each conflict has associated a competence and the information about the conflicts and their competences is retrieved from an ontology which was developed in Protégé. To do so, a NetLogo extension was developed using the Java programming language and the JENA API (to make queries over the ontology).

Peer reviewed Flibs'NLogo - An elementary form of evolutionary cognition

Cosimo Leuci | Published Thu Jan 30 08:34:19 2020

Flibs’NLogo implements in NetLogo modelling environment, a genetic algorithm whose purpose is evolving a perfect predictor from a pool of digital creatures constituted by finite automata or flibs (finite living blobs) that are the agents of the model. The project is based on the structure described by Alexander K. Dewdney in “Exploring the field of genetic algorithms in a primordial computer sea full of flibs” from the vintage Scientific American column “Computer Recreations”
As Dewdney summarized: “Flibs […] attempt to predict changes in their environment. In the primordial computer soup, during each generation, the best predictor crosses chromosomes with a randomly selected flib. Increasingly accurate predictors evolve until a perfect one emerges. A flib […] has a finite number of states, and for each signal it receives (a 0 or a 1) it sends a signal and enters a new state. The signal sent by a flib during each cycle of operation is its prediction of the next signal to be received from the environment”


Bastien RICHARD | Published Fri Dec 20 13:44:16 2019 | Last modified Wed Jan 29 14:40:26 2020

This is a review release: please do not download except for review.

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.

Population dynamics

Marco Janssen | Published Mon Dec 31 00:13:22 2018

Simple population dynamics model used in Introduction to Agent-Based Modeling by Marco Janssen. For more information see

Spatial rangeland model

Marco Janssen | Published Tue Jan 22 01:51:09 2019

Spatial explicit model of a rangeland system, based on Australian conditions, where grass, woody shrubs and fire compete fore resources. Overgrazing can cause the system to flip from a healthy state to an unproductive shrub state. With the model one can explore the consequences of different movement rules of the livestock on the resilience of the system.

The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see

Provided is a landscape of properties where pastoralists make decisions how much livestock they put on their property and how much to suppress fire from occuring. Rangelands can be grass dominated, or unproductive shrubb dominated. Overgrazing and fire suppresion lead to shrub dominated landscapes. What management strategies evolve, and how is this impacted by policies?
The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see

Governing the commons

Marco Janssen | Published Tue Jan 14 17:12:29 2020

Model on the use of shared renewable resources including impact of imitation via success-bias and altruistic punishment.
The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see

Diffusion of innovations

Marco Janssen | Published Tue Jan 14 17:11:41 2020

3 simple models to illustrate diffusion of innovations.
The models are discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see

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