From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial

TL;DR

This tutorial introduces reinforcement learning concepts to undergraduates, emphasizing practical implementation and bridging the gap between theory and real-world applications, especially in quantum control.

Contribution

It provides an accessible, example-driven introduction to RL tailored for students, focusing on practical coding and application in quantum control.

Findings

Enhanced understanding of RL fundamentals for beginners

Practical coding skills for applying RL in quantum control

Bridging theory and practice in reinforcement learning

Abstract

This tutorial is designed to make reinforcement learning (RL) more accessible to undergraduate students by offering clear, example-driven explanations. It focuses on bridging the gap between RL theory and practical coding applications, addressing common challenges that students face when transitioning from conceptual understanding to implementation. Through hands-on examples and approachable explanations, the tutorial aims to equip students with the foundational skills needed to confidently apply RL techniques in real-world scenarios.