ABM | Insight Maker

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).

Agent Based Disease Simulation

Steven D'Alessandro

This model simulates a waterborne illness spread from a central reservoir. It illustrates the combination of System Dynamics (modeling pathogen levels in the reservoir) and Agent Based Modeling.

Make sure to check out the Map display to see the geographic clustering of disease incidence around the reservoir.

Clone of Clone of Reservoir Disease Spread

Pau Fonseca

Learning about random walk

Clone of Random Walk

Tsogbadrakh Banzragch

From Schluter et al 2017 article A framework for mapping and comparing behavioural theories in models of social-ecological systems COMSeS2017 video. See also Balke and Gilbert 2014 JASSS article How do agents make decisions? (recommended by Kurt Kreuger U of S)

Clone of Modelling human behaviour (MoHuB)

Maurice W.

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).

Agent Based Disease Simulation

Steven D'Alessandro

ABM Model Test

ABM Test

Steven D'Alessandro

From IM-3533 Grimm's ODD and Nate Osgood's ABM Modeling Process and Courses based on Volker Grimm and Steven F. Railsback's 2012 paper and Muller et al 2013 paper Describing Human Decisions in Agent-based Models – ODD + D, An Extension of the ODD Protocol', Environmental Modelling and Software, 48: 37-48.

Pattern Oriented Modelling

Geoff McDonnell

3 11 months ago

This model is a classic instance of an Erlang Queuing Process.

We have the entities:

- A population of cars which start off in a "cruising" state;

- At each cycle, according to a Poisson distribution defined by "Arrival Rate" (which can be a constant, a function of time, or a Converter to simulate peak hours), some cars transition to a "looking" for an empty space state.

- If a empty space is available (Parking Capacity > Count(FindState([cars population],[parked]))) then the State transitions to "Parked."

-The Cars stay "parked" according to a Normal distribution with Mean = Duration and SD = Duration / 4

- If the Car is in the state "Looking" for a period longer than "Willingness to Wait" then the state timeouts and transitions to impatient and immediately transitions to "Crusing" again.

The model is set to run for 24 hours and all times are given in hours (or fraction thereof)

WIP:

- Calculate the average waiting time;

- Calculate the servicing level, i.e., 1- (# of cars impatient)/(#cars looking)

A big THANK YOU to Scott Fortmann-Roe for helping setup the model's framework.

Clone of Electric Car Parking

Phillip Jones

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).

Clone of Agent Based Disease Simulation

r mud

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).

Clone of Agent Based Disease Simulation

Guilherme Werpel Fernandes

An overview of this quantitative systems science method based on Kurt Kreuger's workshops for public health

Agent Based Modelling ABM

Geoff McDonnell

Modelo Baseado em Agente para a dispersão espacial de doenças, considerando o modelo SIR com perda da imunidade ao vírus, conforme [Bellinger G.]

Clone of Modelo de dispersão espacial de uma doença baseado em SIR-ABM

Nilo Guimaraes

This Agent-based Model was an idea of Christopher DICarlo "Disease Transmission with Agent Based Model' aims to present the COVID cases in Puerto Princesa City as of June 3, 2021

Insight author: Pia Mae M. Palay

Clone of ABM Model of COVID-19 in Puerto Princesa City

Rojean R. Rosales

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).

Clone of CS558 Agent-Based Spatially Aware Disease Model

Bashier Dahman

Model combining system dynamics and agent based modeling. Based on Prochaska's Transtheoretical Model of Behaviour Change. See also preceding SD Version IM-574

Clone of Clone of Smoking Cessation

Anchal Patil

Model combining system dynamics and agent based modeling. Based on Prochaska's Transtheoretical Model of Behaviour Change. See also preceding SD Version IM-574

Clone of Clone of Smoking Cessation

Ismael Victor Costa

This is my first attempt at creating a simple Agent Based Simulation Model. Nothing fancy, just something that works.

This insight is an element of the Agent Based Modeling learning module in Systems KeLE.

Clone of Your First ABM

Jose Juan Hernandez

Modelo Baseado em Agente para a dispersão espacial de doenças, considerando o modelo SIR com perda da imunidade ao vírus, conforme [Bellinger G.]

Clone of Modelo de dispersão espacial de uma doença baseado em SIR-ABM

Bernardo Coelho de Almeida Resende

Een 'agent based model' voor de capaciteit voor het fixen van software bug. Het bevat drie klassen van bugs: Foutrisico, Fout en Opgelost.

Bugfix-capaciteit Model

Steven van Hekelen

A simple agent based foraging model. Consumer agents will move between fertile patches consuming them.

Clone of Agent Based Foraging Model

Roger Jenkins

7

WIP Combining SD and ABM Representations

Clone of Combined SD and ABM SIR Disease Dynamics

Travis Rhoades

Modelo Baseado em Agente para a dispersão espacial de doenças, considerando o modelo SIR com perda da imunidade ao vírus, conforme [Bellinger G.]

Modelo de dispersão espacial de uma doença baseado em SIR-ABM

Dager Moreira da Silva

3

I used the "disease dynamics" tutorial to help me construct this ABM, in which the individual agents are students and the states in which they can find themselves (with regard to learning a new skill/concept) include "confusion," "familiarity," and "mastery." I modeled the transitions from one state to the next under the assumption that a student cannot transition from "mastery" of a particular concept back to "confusion." This model also operates under the assumption that the more students who become familiar with a skill, the more likely it is that other students will, too (presumably, students help each other).

The skill I imagined being taught to these students is something like Argumentative Writing, as most students can become "familiar" with this skill (or perform "satisfactorily" in it), while only some students are likely to "master" this skill in a given school year.

I labeled the transitions "exposure" and "practice" to signify that exposing students to a new skill/concept tends to lead to their becoming familiar with it, while students taking on the task of practicing is the only way for them to transition to mastery.

I complicated this model by adding a teacher to the mix. I also changed the number of states that students can exhibit in order to make it such that there is a 50/50 chance that once a student has learned a skill, he/she will enter a state of confusion as opposed to familiarity with the new skill/concept. The states that teachers can enter include "helpful" and "overwhelmed." The "overwhelmed" state depends on the number of students who are in a state of confusion (asking too many questions). As students transition to the states of familiarity or mastery, the teacher becomes less overwhelmed and moves back into the state of simply being "helpful."

Clone of First ABM Attempt: Modeling Student Mastery

Jeanette Ling

A simple agent based foraging model. Consumer agents will move between fertile patches consuming them.

Clone of Agent Based Foraging Model

Juan D. Arango

ABM Models