dorsal/arxiv
View SchemaFrom Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial
| Authors | Abhijit Sen, Sonali Panda, Mahima Arya, Subhajit Patra, Zizhan Zheng, Denys I. Bondar |
|---|---|
| Categories | |
| ArXiv ID | 2601.08662vv1 |
| URL | https://arxiv.org/abs/2601.08662 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
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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"date_created": "2026-02-17T05:53:15.699000Z",
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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.",
"arxiv_id": "2601.08662",
"authors": [
"Abhijit Sen",
"Sonali Panda",
"Mahima Arya",
"Subhajit Patra",
"Zizhan Zheng",
"Denys I. Bondar"
],
"categories": [
"cs.AI",
"quant-ph"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner\u0027s Tutorial",
"url": "https://arxiv.org/abs/2601.08662",
"version": "v1"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "0970c10d-3fd3-439c-bd55-5b8fb18a586e",
"id": "arXiv Dataset",
"type": "Model",
"variant": "snapshot-2026-01-17",
"version": "0.1.0"
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