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.

Bibliographische Detailangaben
Hauptverfasser: Saha, Prashanta Kumar, Saha, Vishal
Weitere Verfasser: Upoma, Ipshita Bonhi
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Brac University 2021
Schlagworte:
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 Zugang:http://hdl.handle.net/10361/15680

Online

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

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