3D Ecosystem Simulation

This repository contains a simulation of a 3D ecosystem where prey, predators, and resources interact. The simulation uses the Agents.jl package for agent-based modeling and CairoMakie.jl for visualization. Organisms evolve through mutation and reproduction, and their behavior is determined by their genome, energy levels, and surroundings.

initial_simulation_2k_timesteps.mp4

Features

• Organism Types: Prey and predators with unique traits (speed, sensing range, energy efficiency).
• Resources: Energy sources that prey can consume.
• Genetic Mutation: Offspring inherit mutated versions of their parent's genome.
• Behavior: Prey avoid predators and move toward resources; predators hunt prey.
• Visualization: Dynamic 3D visualization of the ecosystem with energy-based coloring.

Requirements

To run this simulation, you need the following Julia packages installed:

• LinearAlgebra
• Distributions
• CairoMakie
• Agents
• Colors
• ColorSchemes

How to Run

1. Clone the Repository:

   git clone <repository_url>
   cd <repository_folder>

2. Install Required Packages: Open a Julia REPL and run:

   using Pkg
   Pkg.add(["LinearAlgebra", "Distributions", "CairoMakie", "Agents", "Colors", "ColorSchemes"])

3. Run the Simulation: Load the script in Julia and execute the make_vid(fig) function to generate a video of the simulation:

   include("simulation.jl")
   make_vid(fig)

   The simulation video will be saved as simulation.mp4.

Simulation Details

Agent Structure

Each organism is an agent defined as follows:

@agent struct Organism3D(ContinuousAgent{3,Float64})
    species::Symbol  # :prey or :predator
    energy::Float64  # Current energy level
    genome::Vector{Float64}  # [speed, sensing_range, energy_efficiency]
end

Initialization

The ecosystem initializes with:

• A user-defined number of prey, predators, and resources.
• Prey and predators are randomly placed in a 3D space of size (100, 100, 100).

Behavior

• Prey: Move toward nearby resources or away from predators.
• Predators: Hunt prey within their sensing range.
• Reproduction: Organisms reproduce when their energy exceeds a threshold.
• Energy Management: Organisms lose energy based on their speed and efficiency. Prey gain energy by consuming resources, and predators gain energy by consuming prey.

Visualization

• Colors: Organisms are colored based on their energy level (green = high, red = low).
• Shapes: Prey are represented as circles, and predators as triangles.
• Resources: Displayed as light cyan hexagons.

Output

The simulation creates an MP4 video (simulation.mp4) that visualizes the ecosystem dynamics over time.

Parameters

You can modify these parameters in the initialize_model function:

• n_prey: Number of prey.
• n_predators: Number of predators.
• n_resources: Number of resource pools.
• extent: Size of the simulation space.

Example:

model, resources = initialize_model(n_prey=20, n_predators=5, n_resources=50, extent=(150.0, 150.0, 150.0))

Example Video

The resulting video shows prey avoiding predators, predators hunting prey, and resources being consumed, leading to emergent ecosystem dynamics.

License

This project is licensed under the MIT License.

Contributions

Contributions and suggestions are welcome! Please feel free to open issues or submit pull requests.

Acknowledgments

• Agents.jl for agent-based modeling.
• CairoMakie.jl for visualization.