This project was started as an education exercise to teach me more about Genetic Algorithms in preparation for my proposed dissertation topic.
Most of the structure of the code was adapted from the book 'Genetic Algorithms in search, Optimization and Machine Learning' by David E. Goldberg, where it was written in Pascal.
In order to better understand how to piece together an algorithm like this I decided to try and adapt and improve the design into a modern language like Python.
In this case the genetic algorithm uses a binary string and tried to find the largest value it can make when that binary string is converted to decimal.
The user can input their desired Population, String and Generation Size along with the Crossover and Mutation probability, allowing experimentation in order to better understand the GA mechanics
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