Dynamic modularity
Geoff McDonnell ★
- 2 years 5 months ago
The Tyranny of small steps archetype (agent based)
H Haraldsson
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
- 6 years 5 months ago
ABM Test
Gene Bellinger
- 2 years 7 months ago
Estacionamento
Simulação Computacional
We have the entities:- A population of cars which start off in a "crusing" 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.
- 7 years 5 months ago
First ABM Attempt: Modeling Student Mastery
Kate Glassman
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."
- 5 years 2 months ago
42845270: Nathaniel Vala_ Assignment 3
Nathaniel Vala
- 5 years 3 months ago
Random Walk2
Ming Li
- 3 years 8 months ago
Butterfly Corridors
Ash Moran ★
Model ODD: http://www.railsback-grimm-abm-book.com/Chapter04/ButterflyModelODD.txt
- 6 years 9 months ago
Modelo Híbrido (SD e ABM) de Atendimento Médico de Emergência
Simulação Computacional
Health Care Emergency Patient Flow Work ABM Regional Services Clinical Care
- 7 years 5 months ago
Juego de la Vida (clonado)
Denny S. Fernandez del Viso
An implementation of the classic Game of Life (original de Scott Fortmann-Roe 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.
- 5 years 1 month ago
CS558 Agent-Based Spatially Aware Disease Model
Ray Madachy
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).
- 10 months 1 week ago
Agent-Based Disease Dynamics
Gavin McNicol
- 7 years 9 months ago
Undergraduate curriculum model 1
Joe LeDoux
We have the entities:- A population of cars which start off in a "crusing" 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.
- 7 years 5 months ago
Clone of Smoking Cessation
Geoff McDonnell ★
- 3 years 11 months ago
Agent Based Disease Simulation
Dusan Pavlovic
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).
- 3 years 8 months ago
Modelling the effect of street trees
Jian Song
- 4 years 4 months ago
Simulating the Ashes Test Series
Ben
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
- 7 years 5 months ago
CS558 Random Walk Agent-Based and Continuous Model
Ray Madachy
- 10 months 1 week ago
Clone of Modelling human behaviour (MoHuB)
Peter van Doesburg
Environment Economics Framework Behavior Decision-Making Agent ABM Learning PCT
- 2 years 5 months ago
Accident warning through VANET
Abhinav Kapoor
- 7 years 7 months ago
Obesity BMI dynamics
Geoff McDonnell ★
- 4 years 7 months ago
Clone of Fear Conditioning 3 Agents with Spatial Patches
Peter Addor ★
- 6 years 1 month ago
Modelo de dispersão espacial de uma doença baseado em SIR-ABM
Dager Moreira da Silva
Modelo Baseado em Agente para a dispersão espacial de doenças, considerando o modelo SIR com perda da imunidade ao vírus, conforme [Bellinger G.]
- 5 months 2 weeks ago
Agent Based Disease Simulation
Steven D'Alessandro ★
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).
- 3 months 1 week ago