This is my first attempt at creating a simple Agent Based Simulation Model. Nothing fancy, just something that works.

Demo of population growth with distinct agents.

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

A new archetype, The Tyranny of Small Steps (TYST) has been observed. Explained through a system dynamics perspective, the archetypical behaviour TYST is an unwanted change to a system through a series of small activities that may be independent from one another. These activities are small enough not to be detected by the ‘surveillance’ within the system, but significant enough to encroach upon the “tolerance” zone of the system and compromise the integrity of the system. TYST is an unintentional process that is experienced within the system and made possible by the lack of transparency between an overarching level and a local level where the encroachment is taking place.

Reference:

Haraldsson, H. V., Sverdrup, H. U., Belyazid, S., Holmqvist, J. and Gramstad, R. C. J. (2008), The Tyranny of Small Steps: a reoccurring behaviour in management. Syst. Res., 25: 25–43. doi: 10.1002/sres.859 

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

Tutorial model of disease dynamics using ABM

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.

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

Mammal modelling

This is my first attempt at creating a simple Agent Based Simulation Model. Nothing fancy, just something that works.

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).

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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).

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).

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 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 random walk demonstration using an ABM.

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).