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.

WIP based on previous work on obesity

First attempt at transition between multiple states

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.

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

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

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.

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

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. 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.

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 IM-3533 Grimm's ODD and Nate Osgood's ABM Modeling Process and Courses based on Volker Grimm and Steven F. Railsback's 2012 paper and Muller et al 2013 paper Describing Human Decisions in Agent-based Models – ODD + D, An Extension of the ODD Protocol', Environmental Modelling and Software, 48: 37-48.

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 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 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.

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 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).

Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of IM-14982 combined with IM-17598 and IM-9773