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.

Detalles Bibliográficos
Autores principales: Saha, Prashanta Kumar, Saha, Vishal
Otros Autores: Upoma, Ipshita Bonhi
Formato: Tesis
Lenguaje:English
Publicado: Brac University 2021
Materias:
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
Acceso en línea:http://hdl.handle.net/10361/15680

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