MicroWorld

A genetic algorithm-based life simulation where organisms navigate a digital ecosystem, compete for resources, and evolve through genetic inheritance. Watch as digital entities develop behaviors through genome-driven decision-making.

MicroWorld is a real-time simulation of artificial organisms controlled by genetic algorithms. Each entity is a small creature with a 64-byte genome that encodes behaviors such as movement, energy consumption, reproduction, and predation. The simulation demonstrates how environmental pressures and genetic traits influence population dynamics.

Features

🧬 Genetic-Driven Behavior

Each organism is controlled by a 64-byte genome that dictates its behavioral decisions:

• Rotation & Movement - Navigate through the environment based on genetic instructions
• Sensing - Look ahead to detect obstacles, food, and other entities
• Photosynthesis - Passively generate energy from the environment
• Predation - Hunt and consume other organisms for energy
• Reproduction - Create offspring when sufficient energy is accumulated

🌍 Dynamic Environment

• Grid-based World - entity cells in a 1280×720 pixel environment
• Energy Systems:
  • Light Energy - Available through photosynthesis
  • Organic Energy - Obtained by consuming other entities
  • Division Energy - Required to reproduce
• Entity Relationships - Track friends (relatives), enemies, and empty spaces
• Collision Detection - Environmental boundaries and entity interactions

👁️ Sensory System

Organisms can:

• Look ahead at adjacent positions to sense their surroundings
• Identify empty cells, walls, relatives, and enemies
• React to detected entities based on genetic programming

🔄 Population Dynamics

• Multiple Phenotypes - Pre-configured genome patterns create different organism types (herbivores, hunters, standard)
• Random Mutations - Each organism starts with a randomized genome
• Heredity - Offspring inherit genetic traits from their parent
• Population Tracking - Monitor alive, dead, and total entity counts in real-time
• Natural Selection - Organisms that fail to adapt die, pruning unsuccessful strategies

🎯 Behavioral Genetics

The simulation includes several starter genotypes:

• Passive Organism - Relies on photosynthesis
• Hunter - Aggressive predatory behavior
• Left-turning, Top-turning, Right-turning, Bottom-turning - Directional movement patterns

Visuals

How It Works

1. Initialization - The simulation starts with 3 randomly-generated organisms
2. Genome Execution - Each step, active organisms execute genetic instructions (up to 10 steps per cycle)
3. Energy Management - Actions consume energy; reproduction and death manage population
4. Real-time Feedback - Console displays live counts: Alive, Dead, and Total entities
5. Game Over Condition - Simulation ends when all organisms die or only one type remains

Behaviors Available to Organisms

Each behavior in the genome can be triggered by instruction codes:

• Rotate - Change facing direction (up, down, left, right)
• Move - Advance in current direction
• Look - Sense adjacent cells for resources and entities
• Photosynthesis - Gain light energy passively
• Division - Reproduce when energy threshold is met
• Eat - Consume encountered organisms

Build Requirements

• C++ compiler (Visual Studio recommended for .vcxproj)
• SFML graphics library
• Standard C++ library