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

Health Care Emergency Patient Flow Work ABM Regional Services Clinical Care

The VANET handles situation of parking in crowded areas. It takes into account the parking capacity, arrival rate of cars, already parked cars , while making decisions.
 The description of states are :


1. Cruising : State of cars which are moving out of parking area, but are still inside the parking lot.

2.Parked : State of cars which are already parked.

3. Just entered : State of cars which have just entered the parking lot and are searching for parking position.

Erlang 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.
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ABM KeLE ABM

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

Health Care Methods Hybrid ABM Decision Making EHealth Technology Systems Engineering Complexity Forrester

ABM

This is my first attempt

ABM

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

ABM KeLE ABM

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

Health Care Methods Hybrid ABM Decision Making EHealth Technology Systems Engineering Complexity Forrester

WIP Combining SD and ABM Representations

Hybrid ABM Feedback

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

Health Care Prevention Smoking Hybrid Behavior ABM

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).

ABM KeLE ABM

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

ABM KeLE 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). 
The skill I imagined being taught to these students is something like Argumentative Writing, as most students can become "familiar" with this skill (or perform "satisfactorily" in it), while only some students are likely to "master" this skill in a given school year. 
I labeled the transitions "exposure" and "practice" to signify that exposing students to a new skill/concept tends to lead to their becoming familiar with it, while students taking on the task of practicing is the only way for them to transition to mastery. 
I complicated this model by adding a teacher to the mix. I also changed the number of states that students can exhibit in order to make it such that there is a 50/50 chance that once a student has learned a skill, he/she will enter a state of confusion as opposed to familiarity with the new skill/concept. The states that teachers can enter include "helpful" and "overwhelmed." The "overwhelmed" state depends on the number of students who are in a state of confusion (asking too many questions). As students transition to the states of familiarity or mastery, the teacher becomes less overwhelmed and moves back into the state of simply being "helpful."  

ABM

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

ABM KeLE ABM

Based on Nate Osgood's April 2014 Singapore Presentation Youtube video and Lyle Wallis material Gojii at DecisioTech See also Complex Decison Technologies IM as a more polished version

Health Care Methods Behavior Hybrid ABM Decision Making Causation Complexity Systems Engineering Multiscale

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). 
The skill I imagined being taught to these students is something like Argumentative Writing, as most students can become "familiar" with this skill (or perform "satisfactorily" in it), while only some students are likely to "master" this skill in a given school year. 
I labeled the transitions "exposure" and "practice" to signify that exposing students to a new skill/concept tends to lead to their becoming familiar with it, while students taking on the task of practicing is the only way for them to transition to mastery. 
I complicated this model by adding a teacher to the mix. I also changed the number of states that students can exhibit in order to make it such that there is a 50/50 chance that once a student has learned a skill, he/she will enter a state of confusion as opposed to familiarity with the new skill/concept. The states that teachers can enter include "helpful" and "overwhelmed." The "overwhelmed" state depends on the number of students who are in a state of confusion (asking too many questions). As students transition to the states of familiarity or mastery, the teacher becomes less overwhelmed and moves back into the state of simply being "helpful."  

ABM

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).

ABM KeLE ABM

This is my first attempt at creating a simple Agent Based Simulation Model. Nothing fancy, just something that works.
If you find these contributions meaningful your sponsorship would be greatly appreciated.

ABM KeLE ABM

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).

ABM KeLE ABM

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.

ABM KeLE ABM

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.

ABM KeLE ABM

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

ABM KeLE ABM

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).

ABM KeLE ABM

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).

ABM Disease