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

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).

Three Agent Model of  IM-13669 . Unconscious affective dynamics Josh Epstein's Agent Zero Book  webpage   See spatial patches version  IM-15119    
Three Agent Model of IM-13669. Unconscious affective dynamics Josh Epstein's Agent Zero Book webpage 
See spatial patches version IM-15119
 
Model combining system dynamics and agent based modeling. Based on Prochaska's Transtheoretical Model of Behaviour Change. See also preceding SD Version  IM-574
Model combining system dynamics and agent based modeling. Based on Prochaska's Transtheoretical Model of Behaviour Change. See also preceding SD Version IM-574
 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.

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

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

 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.

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.
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 .
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.
 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).

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).

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

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

 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).

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).

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)
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)
 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).

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).

 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).

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).

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

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

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

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

 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).

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).

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

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