ABM | Insight Maker

WIP Combining SD and ABM Representations

Clone of Combined SD and ABM SIR Disease Dynamics

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

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 Reservoir Disease Spread

Geoff McDonnell

7

当处在春节时期，疫情来临时，外来人口较多的S市的疫情传染仿真模型。

人群的状态可分为S/E/I/R/D的五个状态，S为易感染者（即S市所在人群），E为潜伏期患者（人群不会对他远离，但是会传染他人），I为感染者（为医院确诊人群，他人会远离该患者），R为康复人群，D为死亡人群。

SEIR

Allen Zhang

First attempt at transition between multiple states

Clone of OA knee multiple state ABM

Ruri

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."

First ABM Attempt: Modeling Student Mastery

Kate Glassman

10

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

We have the entities:

- A population of cars which start off in a "crusing" 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 Estacionamento

Ray Madachy

21

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 et adapté de

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

Épidémie Multi-Agents

France Caron

Will the ducks make it to the pond? or will the hawks swoop on them?

Duck v Hawk v3

Bruce Schneider

4

WIP Ideas for a hybrid budding SD plus ABM depression dynamics model

Clone of Hybrid Depression Dynamics Model

Warih Puspitasari

Model a board game

HW5.1

Jeremiah Krick

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

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

Clone of Foraging Model

Nathaniel Vala

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

3бөлім Агент

Gauhar Mukhameddamin

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: Jolina Rosile Magbanua

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

Rojean R. Rosales

Three Agent Model of IM-14058 with Spatial awareness. Unconscious affective dynamics Josh Epstein's Agent Zero Book webpage Part II p.89 with spatial ABM. See next version at IM-15690

Fear Conditioning 3 Agents with Spatial Patches

Geoff McDonnell

Tutorial model of disease dynamics using ABM

Clone of Agent-Based Disease Dynamics

Rodrigo

A simple Susceptible - Infected - Recovered disease as a stock and flow model.

@LinkedIn, Twitter, YouTube

SIR Disease Model

Gene Bellinger

7

Physician agents interacting with delegate agents for emergency department assessment diagnosis and treatment. From BMC paper May 2013, combining figs 1 and 2

ED Physician Delegation Hybrid Model

Geoff McDonnell

Clusters of interacting methods for improving health services network design and delivery. Simplified version of IM-14982 combined with IM-17598 and IM-9773

Clone of Complex Decision Technologies

lee gwo guang

ABM Model Test

@LinkedIn, Twitter, YouTube

ABM Test

Gene Bellinger

3

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

We have the entities:

- A population of cars which start off in a "crusing" 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 Clone of Parking Lot Problem (WIP)

Lynard Misa

Hybrid conceptual mapping of relationships involving system causal loop diagram linked with ABM. Output of the problem conceptualization phase of the modelling process prior to developing a computational hybrid model in AnyLogic. Includes Nate Osgood's O PARTIES extension of Ross Hammond's PARTE

Clone of Conceptual map of hybrid CLD and ABM

Luis R Matos

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

ABM Model of COVID-19 in Puerto Princesa City

Pia Mae Palay

11

ABM Models