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Gist of Agents.jl introductory workshop
### Step 1: decide space
using Agents
space = GridSpace((10, 10); periodic = false)
### Step 2: make agent type
mutable struct SchellingAgent <: AbstractAgent
id::Int
pos::NTuple{2, Int}
group::Int
happy::Bool
end
### Step 3: make model
properties = Dict(:min_to_be_happy => 3)
scheduler = Schedulers.by_property(:group)
schelling = ABM(SchellingAgent, space; properties)
using Random # for reproducibility
function initialize(; N = 320, M = 20, min_to_be_happy = 3, seed = 125)
space = GridSpace((M, M), periodic = false)
properties = Dict(:min_to_be_happy => min_to_be_happy)
rng = Random.MersenneTwister(seed)
model = ABM(
SchellingAgent, space;
properties, rng, scheduler = Schedulers.randomly
)
for n in 1:N
agent = SchellingAgent(n, (1, 1), n < N / 2 ? 1 : 2, false)
add_agent_single!(agent, model)
end
return model
end
### Step 4: Agent stepping function and step!
function agent_step!(agent, model)
minhappy = model.min_to_be_happy
count_neighbors_same_group = 0
for neighbor in nearby_agents(agent, model)
if agent.group == neighbor.group
count_neighbors_same_group += 1
end
end
if count_neighbors_same_group minhappy
agent.happy = true
else
move_agent_single!(agent, model)
end
return
end
model = initialize()
step!(model, agent_step!)
step!(model, agent_step!, 3)
### Step 5: visualization
using InteractiveDynamics, GLMakie
groupcolor(a) = a.group == 1 ? :blue : :orange
groupmarker(a) = a.group == 1 ? :circle : :rect
fig, _ = abmplot(model; ac = groupcolor, am = groupmarker, as = 10)
display(fig)
model = initialize();
abmplot(
model, agent_step!, dummystep;
ac = groupcolor, am = groupmarker, as = 10,
title = "Schelling's segregation model"
)
### Step 6: Collecting data
adata = [:happy, :group]
model = initialize()
data, _ = run!(model, agent_step!, 5; adata)
x(agent) = agent.pos[1]
model = initialize()
adata = [x, :happy]
data, _ = run!(model, agent_step!, 5; adata)
using Statistics: mean
model = initialize();
adata = [(:happy, sum), (x, mean)]
data, _ = run!(model, agent_step!, 5; adata)
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