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.

Dades bibliogràfiques
Autors principals: Saha, Prashanta Kumar, Saha, Vishal
Altres autors: Upoma, Ipshita Bonhi
Format: Thesis
Idioma:English
Publicat: Brac University 2021
Matèries:
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
Accés en línia:http://hdl.handle.net/10361/15680

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