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System Dynamics Models

System Dynamics is a powerful approach for modeling change within systems and Insight Maker is perfect for building System Dynamics models.

Agent Based Models

Explore the interactions between dynamic agents. Use Insight Maker to define agent behavior and simulate a population of agents interacting.

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Explore powerful simulation algorithms for System Dynamics and Agent Based Modeling. Use System Dynamics to gain insights into your system and Agent Based Modeling to dig into the details. Types of Modeling

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Explore What Others Are Building

Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.

Model for illustrating system dynamics in course "Understanding the Climate Crisis. Economic Perspectives on Drivers and Solutions" at University Bremen, Summer Term 2026

Campus Cycling SD Model

Wolf Rogowski

4 days ago

World4 is a predictive model for world population. Population has grown hyper-exponentially in the last millenium, with the doubling time decreasing from 900 years in 1000 CE to a minimum of ~35 years in 1963 CE. Technology is defined as that which decreases the death rate and/or increases the effective birth rate (i.e. by decreasing infant mortality). Technology grows exponentially, therefore population fits a hyper-exponential (exponent within an exponent). Models for the end of growth are explored using equations that express the ways humans are depleting Earth's biocapacity, the nature of resource depletion, and the relationship between natural resources and human carrying capacity. This simple model, containing just two closed systems, captures the subtle shifts in the population trajectory of the last 50 years. Specifically, hyperexponential growth has given way to subexponential growth. A peak is predicted for the time around 2028. [Bystroff, C. (2021). Footprints to singularity: A global population model explains late 20th century slow-down and predicts peak within ten years. PloS one, 16(5), e0247214.]

World4.5

Christopher Bystroff

22 7 months ago

Example from book "Complex System Research in Psychology" by Han van der Maas (https://santafeinstitute.github.io/ComplexPsych/)

Romeo & Juliet

Kyra Evers

4 months ago

A spatially aware, agent based model of disease spread. There are three classes of people: susceptible (healthy), infected (sick and infectious), and recovered (healthy and temporarily immune).

@LinkedIn, Twitter, YouTube

Spatially Aware SIR Disease Model

Gene Bellinger

Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:

http://www.nku.edu/~longa/classes/2020spring/mat375/mathematica/SIRModel-MAA.nb
https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death

Andrew E Long

STEM-SM combines a simple ecosystem model (modified version of VSEM; Hartig et al. 2019) with a soil moisture model (Guswa et al. (2002) leaky bucket model). Outputs from the soil moisture model influence ecosystem dynamics in three ways.

(1) The ratio of actual transpiration to maximum evapotranspiration (T/ETmax) modifies gross primary productivity (GPP).

(2) Degree of saturation of the soil (Sd) modifies the rate of soil heterotrophic respiration.

(3) Water limitation of GPP (by T/ETmax) and of soil nutrient availability (approximated by Sd) combine with leaf area limitation (approximated by fraction of incident photosynthetically-active radiation that is absorbed) to modify the allocation of net primary productivity to aboveground and belowground parts of the vegetation.

Ecosystem dynamics in turn influence flows of water in to and out of the soil moisture stock. The size of the aboveground biomass stock determines fractional vegetation cover, which modifies interception, soil evaporation and transpiration by plants.

References:

Guswa, A.J., Celia, M.A., Rodriguez-Iturbe, I. (2002) Models of soil moisture dynamics in ecohydrology: a comparative study. Water Resources Research 38, 5-1 - 5-15.

Hartig, F., Minunno, F., and Paul, S. (2019). BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics. R package version 0.1.7. https://CRAN.R-project.org/package=BayesianTools

Simple Terrestrial Ecosystem Model - Soil Moisture (STEM-SM)

Lisa Belyea

226