Genetic Algorithm Robots Simulation

Overview

The GARobot simulation is a C++ program that models a population of robots navigating a randomly generated map to harvest resources. Each robot has a set of genetic traits that influence its movement and decision-making process. The simulation iterates through multiple generations, where the best-performing robots contribute their genes to the next generation.

Features

• Generates a 10x10 grid map with random obstacles.
• Creates an initial population of 200 robots with genetic traits.
• Robots move on the map, harvesting power and avoiding obstacles.
• Tracks and averages the performance of robots across multiple generations.
• Uses a genetic algorithm approach to evolve robot traits over generations.

Classes

genMap

• Attributes:
  • int map[10][10]: A 2D array representing the map.
• Methods:
  • void newMap(): Generates a new map with random obstacles.
  • void mapPrint(): Prints the current state of the map.
  • int getValue(int i, int j): Retrieves the value at coordinates (i, j).
  • int changeValue(int i, int j, int k): Changes the value at coordinates (i, j) to k.

genBot

• Attributes:
  • int bots[200][16][5]: A 3D array representing the genetic traits of 200 robots.
• Methods:
  • void setGenes(): Initializes random genes for the robots.
  • void genPrint(): Prints the genes of all robots.
  • void botPrint(int i): Prints the genes of a specific robot.
  • int getValue(int i, int j, int k): Retrieves a specific gene value.
  • int changeValue(int i, int j, int k, int n): Changes a specific gene value.

Compilation

To compile the code, use a C++ compiler. For example, you can use g++:

g++ GARobot.cpp -o GARobot