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.

Bibliografische gegevens
Hoofdauteurs: Saha, Prashanta Kumar, Saha, Vishal
Andere auteurs: Upoma, Ipshita Bonhi
Formaat: Thesis
Taal:English
Gepubliceerd in: Brac University 2021
Onderwerpen:
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 toegang:http://hdl.handle.net/10361/15680

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