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

Fuente: arXiv
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Main Authors: Sen, Abhijit, Panda, Sonali, Arya, Mahima, Patra, Subhajit, Zheng, Zizhan, Bondar, Denys I.
Format: Preprint
Published: 2026
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author Sen, Abhijit
Panda, Sonali
Arya, Mahima
Patra, Subhajit
Zheng, Zizhan
Bondar, Denys I.
author_facet Sen, Abhijit
Panda, Sonali
Arya, Mahima
Patra, Subhajit
Zheng, Zizhan
Bondar, Denys I.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2601_08662
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial
Sen, Abhijit
Panda, Sonali
Arya, Mahima
Patra, Subhajit
Zheng, Zizhan
Bondar, Denys I.
Artificial Intelligence
Quantum Physics
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.
title From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial
topic Artificial Intelligence
Quantum Physics
url https://arxiv.org/abs/2601.08662