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

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

Clone of Clone of Agent Based Foraging Model
Maicom Peters Xavier
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)
ABM Environment Economics Framework Behavior Decision-Making Agent Learning PCT
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)
Clone of Modelling human behaviour (MoHuB)
Peter van Doesburg
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 parki
Erlang ABM
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.


Clone of PARKING through VANET
Mark Clements
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 .
KeLE ABM 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.

Follow us on YouTube, Twitter, LinkedIn and please support Systems Thinking World.
Clone of Random Walk ABM
Cilem Bozdemir
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
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."  
Clone of First ABM Attempt: Modeling Student Mastery
Jeanette Ling
A simple agent based foraging model. Consumer agents will move between fertile patches consuming them.
KeLE ABM ABM

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

Clone of Agent Based Foraging Model
sub cribed
Modelo Baseado em Agente para a dispersão espacial de doenças, considerando o modelo SIR com perda da imunidade ao vírus, conforme [Bellinger G.]
DOENÇAS SIR ABM

Modelo Baseado em Agente para a dispersão espacial de doenças, considerando o modelo SIR com perda da imunidade ao vírus, conforme [Bellinger G.]

Clone of Modelo de dispersão espacial de uma doença baseado em SIR-ABM
Nilo Guimaraes
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
ABM
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.
Clone of Electric Car Parking
Phillip Jones
A simple agent based foraging model. Consumer agents will move between fertile patches consuming them.
ABM

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

Bacterial resource consumption (ABM)
TDebord
WIP Combining SD and ABM Representations
ABM Hybrid Feedback
WIP Combining SD and ABM Representations
Clone of Clone of Combined SD and ABM SIR Disease Dynamics
Nilo Guimaraes
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).
KeLE ABM 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).

Clone of Agent Based Disease Simulation
Marshall O'Moore
From Schluter et al 2017  article  A framework for mapping and comparing behavioural theories in models of social-ecological systems   See also Balke and Gilbert 2014 JASSS  article  How do agents make decisions? (recommended by Kurt Kreuger U of S)
ABM PCT Learning Agent Decision-Making Behavior Environment Framework Economics
From Schluter et al 2017 article A framework for mapping and comparing behavioural theories in models of social-ecological systems See also Balke and Gilbert 2014 JASSS article How do agents make decisions? (recommended by Kurt Kreuger U of S)
Clone of Modelling human behaviour (MoHuB)
Peter van Doesburg
Demo of population growth with distinct agents. Follow us on YouTube , Twitter , LinkedIn and please support Systems Thinking World .
ABM KeLE ABM
Demo of population growth with distinct agents.

Follow us on YouTube, Twitter, LinkedIn and please support Systems Thinking World.
Clone of Agent Population
Alexandria LeClerc
Insight diagram
ABM
Untitled Insight
Andrey
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. @ LinkedIn ,  Twitter ,  YouTube
Roam Life 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.
Clone of The Game of Life
Christopher Brown
当处在春节时期，疫情来临时，外来人口较多的S市的疫情传染仿真模型。 人群的状态可分为S/E/I/R/D的五个状态，S为易感染者（即S市所在人群），E为潜伏期患者（人群不会对他远离，但是会传染他人），I为感染者（为医院确诊人群，他人会远离该患者），R为康复人群，D为死亡人群。
ABM Disease
当处在春节时期，疫情来临时，外来人口较多的S市的疫情传染仿真模型。
人群的状态可分为S/E/I/R/D的五个状态，S为易感染者（即S市所在人群），E为潜伏期患者（人群不会对他远离，但是会传染他人），I为感染者（为医院确诊人群，他人会远离该患者），R为康复人群，D为死亡人群。
SEIR
Allen Zhang
This is my first attempt at creating a simple Agent Based Simulation Model. Nothing fancy, just something that works. @ LinkedIn ,  Twitter ,  YouTube
ABM Roam
This is my first attempt at creating a simple Agent Based Simulation Model. Nothing fancy, just something that works.
2.2 part
Айдана Елібай
WIP Combining SD and ABM Representations
Hybrid Feedback ABM
WIP Combining SD and ABM Representations
Clone of Combined SD and ABM SIR Disease Dynamics
Jingting REN
This model is a classic instance of an Erlang Queuing Process. 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 simu
ABM Erlang
This model is a classic instance of an Erlang Queuing Process.

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.
Clone of Estacionamento
Igor Benić
Uma implementação do clássico Game of Life usando modelagem baseada em agentes. Regras: Uma célula viva com menos de dois vizinhos vivos morre. Uma célula viva com mais de três vizinhos vivos morre. Uma célula morta com três vizinhos se torna viva.
KeLE ABM ABM

Uma implementação do clássico Game of Life usando modelagem baseada em agentes.

Regras:
  • Uma célula viva com menos de dois vizinhos vivos morre.
  • Uma célula viva com mais de três vizinhos vivos morre.
  • Uma célula morta com três vizinhos se torna viva.
MBA 04 The Game of Life
Ismael Victor Costa
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.
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.
Clone of CS558 Random Walk Agent-Based and Continuous Model
Armando Perez
Learning about random walk
ABM
Learning about random walk
Clone of Random Walk
Tsogbadrakh Banzragch
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).
KeLE ABM 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).

Clone of Agent Based Disease Simulation
Gabriele Cesar Iwashima
A simple agent based foraging model. Consumer agents will move between fertile patches consuming them.
KeLE ABM ABM

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

Clone of Agent Based Foraging Model
Midiev