Maze Solver

Consider a scenario where a walker agent is stuck in a maze. Finding the shortest path through an arbitrary maze or map is simulated using a Pathfinding.Pathfinder and its walkable map property.

Setup

using Agents, Agents.Pathfinding
using FileIO # To load images you also need ImageMagick available to your project

The Walker agent needs no special property, just the id and position from @agent.

@agent Walker GridAgent{2} begin end

The maze is stored as a simple .bmp image, where each pixel corresponds to a position on the grid. White pixels correspond to walkable regions of the maze.

function initalize_model(map_url)
    # Load the maze from the image file. White values can be identified by a
    # non-zero red component
    maze = BitArray(map(x -> x.r > 0, load(download(map_url))))
    # Create a pathfinder by specifying the `walkable` parameter for the pathfinder.
    # Since we are interested in the most direct path to the end, the default
    # `DirectDistance` is appropriate.
    # `diagonal_movement` is set to false to prevent cutting corners by going along
    # diagonals.
    pathfinder = Pathfinder(walkable=maze, diagonal_movement=false)
    # The size of the space is the size of the maze
    space = GridSpace(size(maze); pathfinder, periodic = false)
    model = ABM(Walker, space)
    # Place a walker at the start of the maze
    walker = Walker(1, (1, 4))
    add_agent_pos!(walker, model)
    # The walker's movement target is the end of the maze
    set_target!(walker, (41, 32), model)

    return model
end

initalize_model (generic function with 1 method)

Dynamics

Stepping the agent is a trivial matter of calling move_along_route! to move it along it's path to the target.

agent_step!(agent, model) = move_along_route!(agent, model)

agent_step! (generic function with 1 method)

Visualization

Visualizing the Walker move through the maze is handled through InteractiveDynamics.abm_plot.

using InteractiveDynamics
using CairoMakie

# Our sample walkmap
map_url =
    "https://raw.githubusercontent.com/JuliaDynamics/" *
    "JuliaDynamics/master/videos/agents/maze.bmp"
model = initalize_model(map_url)

AgentBasedModel with 1 agents of type Walker
 space: GridSpace with size (41, 41), metric=chebyshev, periodic=false, pathfinder=A* in 2 dimensions, orthogonal, ϵ=0.0, metric=DirectDistance
 scheduler: fastest

The heatarray keyword argument allows plotting the maze as a heatmap behind the agent.

abm_video(
    "maze.mp4",
    model,
    agent_step!;
    resolution=(700,700),
    frames=310,
    framerate=30,
    ac=:red,
    as=11,
    heatarray = model -> walkmap(model),
    add_colorbar = false,
)