Evolving Novel Sorting Algorithms: A Deep Dive into Neuro Evolution and Reinforcement Learning

Introduction

Sorting algorithms are the backbone of computer science, fundamental to data organization, search optimization, and efficient computation. Traditional algorithms like QuickSort, MergeSort, and HeapSort have been meticulously crafted and optimized over decades. But what if we could discover novel sorting methods by leveraging the power of neural networks and evolutionary algorithms?

In this comprehensive exploration, we delve into how neuro evolution — a combination of neural networks and evolutionary algorithms — can be used to evolve new sorting strategies. I will:

• Introduce the problem setup and objectives.
• Detail the neural network architecture designed to discover novel sorting methods.
• Explain how reinforcement learning and neuro evolution are integrated.
• Discuss the mathematical foundations underpinning the approach.
• Break down the code into sections with rich snippets.
• Compare the evolved methods to traditional sorting algorithms.
• Explore potential use cases for these novel sorting strategies.
• Analyse the results and performance of…