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arXiv · 2601.08662

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

Abhijit Sen·Sonali Panda·Mahima Arya·Subhajit Patra·Zizhan Zheng·Denys I. Bondar
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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.

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Abhijit Sen, Sonali Panda, Mahima Arya, Subhajit Patra, Zizhan Zheng, Denys I. Bondar. 2026-01-13. From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial. https://arxiv.org/abs/2601.08662

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