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).

Clone of Agent Based Disease Simulation

Bechara Assouad

9 months ago

An implementation of the classic Game of Life using agent based modeling.

Rules:

A live cell with less than two alive neighbors dies.
A live cell with more than three alive neighbors dies.
A dead cell with three neighbors becomes alive.

Clone of The Game of Life

Gary Schasteen

An implementation of the classic Game of Life using agent based modeling.

Rules:

A live cell with less than two alive neighbors dies.
A live cell with more than three alive neighbors dies.
A dead cell with three neighbors becomes alive.

Clone of The Game of Life

tiger

Demo of population growth with distinct agents.

Understanding Relationship and Their Implications: The Essence of AND?

Clone of Agent Population

Khorben Boyer

Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of IM-14982 combined with IM-17598 and IM-9773

Clone of Complex Decision Technologies

sub cribed

WIP Combining SD and ABM Representations

Clone of Combined SD and ABM SIR Disease Dynamics

Travis Rhoades

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

Stanislav Kubis

Demo of population growth with distinct agents.

Clone of Agent Population

Felix Huang

The VANET handles situation of parking in crowded areas. It takes into account the parking capacity, arrival rate of cars, already parked cars , while making decisions.
The description of states are :

1. Cruising : State of cars which are moving out of parking area, but are still inside the parking lot.

2.Parked : State of cars which are already parked.

3. Just entered : State of cars which have just entered the parking lot and are searching for parking position.

PARKING through VANET

Abhinav Kapoor

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

Max J Harmon

An implementation of the classic Game of Life using agent based modeling.

Rules:

A live cell with less than two alive neighbors dies.
A live cell with more than three alive neighbors dies.
A dead cell with three neighbors becomes alive.

Clone of The Game of Life

Natty Gur

Demo of population growth with distinct agents.

Follow us on YouTube, Twitter, LinkedIn and please support Systems Thinking World.

Clone of Agent Population

vincent cochet

7

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

Clone of Agent Based Foraging Model

Christopher DiCarlo

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

Based on Nate Osgood's April 2014 Singapore Presentation Youtube video and Lyle Wallis material Gojii at DecisioTech See also Complex Decison Technologies IM as a more polished version

Clone of Complex Intervention Modeling Areas

sub cribed

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

Clone of Agent Based Foraging Model

Luke Emory

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

Clone of Clone of Agent Based Foraging Model

Maicom Peters Xavier

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

Allen Zhang

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

Allen Zhang

Modélisation spatiale et multi-agents d'une épidémie. Avec trois classes d'individus: susceptibles (sains), infectés (malades et contagieux), et remis (sains et temporairement immunisés).

Traduit de

https://insightmaker.com/insight/2846/Agent-Based-Disease-Simulation

Clone of Épidémie Multi-Agents

Igor Belot

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

Jan M Stratil

A random walk demonstration using an ABM. As individuals drink more they become more intoxicated and their walk becomes more random. And when they drink to much it finally kills them.

Follow us on YouTube, Twitter, LinkedIn and please support Systems Thinking World.

Clone of Random Walk ABM

Eric Vargas Loureiro

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