Predefined Models

Predefined agent based models exist in the Models submodule in the form of functions that return model, agent_step!, model_step! when called.

They are accessed like:

using Agents
model, agent_step!, model_step! = Models.flocking(; kwargs...)

The Examples section of the docs outline how to use and interact with each model.

So far, the predefined models that exist in the Models sub-module are:

Agents.Models.flocking — Method

flocking(;
    n_birds = 100,
    speed = 1.0,
    cohere_factor = 0.25,
    separation = 4.0,
    separate_factor = 0.25,
    match_factor = 0.01,
    visual_distance = 5.0,
    dims = (100, 100),
)

Same as in Flock model.

source

Agents.Models.forest_fire — Method

forest_fire(; f = 0.02, d = 0.8, p = 0.01, griddims = (100, 100), seed = 111)

Same as in Forest fire model.

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Agents.Models.schelling — Method

schelling(; numagents = 320, griddims = (20, 20), min_to_be_happy = 3)

Same as in Schelling's segregation model.

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Agents.Models.social_distancing — Method

social_distancing(;
    infection_period = 30 * steps_per_day,
    detection_time = 14 * steps_per_day,
    reinfection_probability = 0.05,
    isolated = 0.5, # in percentage
    interaction_radius = 0.012,
    dt = 1.0,
    speed = 0.002,
    death_rate = 0.044, # from website of WHO
    N = 1000,
    initial_infected = 5,
    seed = 42,
    βmin = 0.4,
    βmax = 0.8,
)

Same as in Continuous space social distancing for COVID-19.

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