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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
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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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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
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If an accident occurs at a place, the master car informs the OBUs of neighbouring cars in group about the accident and they change direction . Some of the cars depending upon their position become master car in other groups and the process of warning is propagated to car population in radius of the accident.
Clone of Accident warning through VANET
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Completion of IM-15119 (which added patches to IM-14058). Unconscious affective dynamics Josh Epstein's Agent Zero Book webpage  Part II p.89 with 2 agent types, spatial patches and location aware, mobile occupying (blue) agents

Clone of Fear Conditioning using 2 Agent types
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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
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
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
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Demo of population growth with distinct agents.

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

Clone of Agent Based Foraging Model
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Modeling User Adoption
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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
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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
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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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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
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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.
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Clone of The Game of Life
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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)
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WIP based on previous work on obesity
Clone of Obesity BMI dynamics
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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)
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Demo of population growth with distinct agents.
Clone of Agent Population
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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
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Clone of Clone of First ABM Attempt: Modeling Student Mastery
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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