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.

Detalhes bibliográficos
Principais autores: Saha, Prashanta Kumar, Saha, Vishal
Outros Autores: Upoma, Ipshita Bonhi
Formato: Tese
Idioma:English
Publicado em: Brac University 2021
Assuntos:
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
Acesso em linha:http://hdl.handle.net/10361/15680

Internet

http://hdl.handle.net/10361/15680

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