MasterMind AI

This repository contains a simple implementation of a MasterMind solver using a genetic algorithm.

The code is divided into two sections: MasterMind modelisation, Genetic algorithm components

Section 1: MasterMind modelisation

This section contains all the basic elements necessary to be able to play around with the general MasterMind game.

I won't go over the rules of the game, you can find them here

Section 2: Genetic algorithm components

This section contains basic genetic algorithm elments including the following:

• Selection
• Mutation
• Crossover

Each component is clearly identifiable and the way each of them work is explained in quite some detail. If you have any experience with AI and/or genetic algorithms, you shouldn't feel lost. If this is new to you, you should still be able to get a general understanding about what's going on.

Running the code

To run the code, simply clone this repository on your machine, open a terminal/cmd, navigate to the cloned folder and run the following: python MasterMind-AI.py

Extra control

There are 7 different parameters that can be modified directly at the command line for you to tailor the behaviour of the program:

• PATTERN_SIZE controls the length of the code that the AI has to guess
• NUMBER_OF_COLOURS controls the number of different "colours" each code can contain
• POPULATION_SIZE controls the number of candidates in each generation
• MAX_GENERATION controls the maximum number of generations produced before taking a guess
• MAX_SIZE controls the maximum amount of eligible candidates per iteration. If the algorithm finds more than MAX_SIZE eligible candidates, it will stop to take a guess
• MUTATION_PROBABILITY controls the probability of mutation in the algorithm
• CROSSOVER_PROBABILITY controls the probability of crossover in the algorithm