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.

Détails bibliographiques
Auteurs principaux: Saha, Prashanta Kumar, Saha, Vishal
Autres auteurs: Upoma, Ipshita Bonhi
Format: Thèse
Langue:English
Publié: Brac University 2021
Sujets:
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
Accès en ligne:http://hdl.handle.net/10361/15680

Internet

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

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