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.

Bibliographic Details
Main Authors: Saha, Prashanta Kumar, Saha, Vishal
Other Authors: Upoma, Ipshita Bonhi
Format: Thesis
Language:English
Published: Brac University 2021
Subjects:
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
Online Access:http://hdl.handle.net/10361/15680

Internet

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

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