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.

Opis bibliograficzny
Główni autorzy: Saha, Prashanta Kumar, Saha, Vishal
Kolejni autorzy: Upoma, Ipshita Bonhi
Format: Praca dyplomowa
Język:English
Wydane: Brac University 2021
Hasła przedmiotowe:
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
Dostęp online:http://hdl.handle.net/10361/15680

Internet

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

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