Exploring the applications of deep reinforcement learning and quantum variational circuit In quantum machine learning

Exploring the applications of deep reinforcement learning and quantum variational circuit In quantum machine learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

書誌詳細
主要な著者:	Saha, Prashanta Kumar, Saha, Vishal
その他の著者:	Upoma, Ipshita Bonhi
フォーマット:	学位論文
言語:	English
出版事項:	Brac University 2021
主題:	Quantum computing Reinforcement learning Quantum Machine Learning (QML) Quantum Variational Circuit (QVC) Deep Q-Network (DQN) Double Deep Q-Network (DDQN) OpenAI Gym IBM-Q TensorFlow Quantum Data mining Quantum theory Machine learning
オンライン･アクセス:	http://hdl.handle.net/10361/15680

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