Evolutionary Robotics Simulation

This project implements a genetic algorithm for evolving robot behaviors.

Main Script: geneticAlgorithm.py

This script runs the main evolutionary simulation.

Key Components:

• Creates an initial population of robots
• Evaluates fitness of individuals
• Implements generational evolution
• Prints population statistics

Usage:

1. Initialize a parent population
2. Evaluate initial fitness
3. Run evolution for a set number of generations
4. Create child populations
5. Evaluate and replace parent population
6. Print final results

Classes

POPULATION

Manages a group of individual robots.

Methods:

• Initialize(): Create initial set of individuals
• Evaluate(show): Assess fitness of individuals
• Print(): Display population information
• Fill_From(parents): Generate new population from parents

INDIVIDUAL

Represents a single robot (implementation not shown in provided code).

ROBOT

Represents the physical robot model (implementation not shown in provided code).

Dependencies

• pyrosim: Likely used for robot simulation
• matplotlib.pyplot: For potential data visualization
• random: For introducing variability
• numpy: For numerical operations
• copy: For object copying
• pickle: For object serialization (not used in shown code)

Usage Example