Insight diagram
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)
Insight diagram
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
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Physician agents interacting with delegate agents for emergency department assessment diagnosis and treatment. From BMC paper May 2013, combining figs 1 and 2
Clone of ED Physician Delegation Hybrid Model
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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
Insight diagram

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

Agent Based Disease Simulation
Insight diagram
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
Insight diagram
A simple Markov chain modeling the transfer of power between two parties in the US Senate. Developed using data from FiveThirtyEight.com for the years 1978-2018.

Transition matrix:

       R   D
R    .7   .3
D    .4   .6


Senate
Insight diagram
Demo of population growth with distinct agents.

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Clone of Agent Population
Insight diagram
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
Insight diagram

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

Clone of Agent Based Foraging Model
Insight diagram
Modeling User Adoption
Insight diagram
The system in which it was possible to vary the number and size of street trees in a city, and to see the concomitant increases and decreases in the amount of pollution in that city.
Street Trees Model
Insight diagram

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

Clone of Clone of Agent Based Foraging Model
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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 Clone of Foraging Model
Insight diagram
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

Clone of Fear Conditioning 3 Agents with Spatial Patches
Insight diagram

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.
If you find these contributions meaningful your sponsorship would be greatly appreciated.
Clone of The Game of Life
Insight diagram
WIP based on previous work on obesity
Clone of Obesity BMI dynamics
Insight diagram
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)
Insight diagram
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)
Insight diagram
Demo of population growth with distinct agents.
Clone of Agent Population
Insight diagram
A Susceptible - Infected - Recovered disease as a stock and flow model for COVID.
COVID SIR Disease Model
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A recent article by a former Australian cricketer got me thinking about how Agent Based Models could help understand how bowlers and batsmen behave in cricket.... 

http://www.theguardian.com/sport/blog/2013/aug/20/ashes-glenn-mcgrath-england-australia

To try and keep things simple I've assumed there are 4 bowlers and 4 batsmen.

There are 2 innings for each side in each game and 5 games in the series, therefore 10 innings for each bowler-batsman combination in the series.

In each innings I model, for each batsman, the following parameters:

- A baseline estimate for how likely each bowler is to get the batsman out in each innings (the baseline varies between batsmen, but is kept constant for each combination for each innings)
- Whether or not the bowler got the batsman out in this innings
- The number of times the bowler has got the batsman out in previous innings
Simulating the Ashes Test Series
Insight diagram
Clone of Clone of First ABM Attempt: Modeling Student Mastery
Insight diagram
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 Clone of Reservoir Disease Spread