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We utilize hybrid quantum deep reinforcement learning to learn navigation tasks for a simple, wheeled robot in simulated environments of increasing complexity.
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Christopher John Cornish Hellaby Watkins · 1989
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Algorithms for Quantum Computation: Discrete Logarithms and Factoring
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Aram W. Harrow, Avinatan Hassidim, and Seth Lloyd · 2009
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Quantum Computation and Quantum Information: 10th Anniversary Edition
Michael A. Nielsen and Isaac L. Chuang · 2010
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Hans J. Briegel and Gemma De las Cuevas · 2012
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Giuseppe Davide Paparo, Vedran Dunjko, Adi Makmal, Miguel Angel Martin-Delgado, and Hans J Briegel · 2014
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A Variational Eigenvalue Solver on a Photonic Quantum Processor
Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alán Aspuru-Guzik, and Jeremy L. O’Brien · 2014
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Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller, Andreas K. Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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Quantum algorithms: an overview
Ashley Montanaro · 2016
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OpenAI Gym, 2016
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Quantum-enhanced machine learning
Vedran Dunjko, Jacob M. Taylor, and Hans J. Briegel · 2016
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Deep Reinforcement Learning with Double Q-Learning
Hado van Hasselt, Arthur Guez, and David Silver · 2016
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The Theory of Variational Hybrid Quantum-Classical Algorithms
Jarrod R. McClean, Jonathan Romero, Ryan Babbush, and Alán Aspuru-Guzik · 2016
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Shixiang Gu, Ethan Holly, Timothy Lillicrap, and Sergey Levine · 2017
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Advances in quantum reinforcement learning
Vedran Dunjko, Jacob M. Taylor, and Hans J. Briegel · 2017
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Proximal policy optimization algorithms, 2017
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, and James Bergstra · 2018
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Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, and Sergey Levine · 2018
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Quantum Computing in the NISQ era and beyond
John Preskill · 2018
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Classification with Quantum Neural Networks on Near Term Processors, 2018
Edward Farhi and Hartmut Neven · 2018
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Richard S. Sutton and Andrew G. Barto · 2018
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Speeding-up the decision making of a learning agent using an ion trap quantum processor
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Sofiene Jerbi, Casper Gyurik, Simon C. Marshall, Hans J. Briegel, and Vedran Dunjko · 2021
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A rigorous and robust quantum speed-up in supervised machine learning
Yunchao Liu, Srinivasan Arunachalam, and Kristan Temme · 2021
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Introduction to quantum reinforcement learning: Theory and pennylane-based implementation
Yunseok Kwak, Won Joon Yun, Soyi Jung, Jong-Kook Kim, and Joongheon Kim · 2021
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Photonic quantum policy learning in openai gym
Dániel Nagy, Zsolt Tabi, Péter Hága, Zsófia Kallus, and Zoltán Zimborás · 2021
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Variational quantum soft actor-critic, 2021
Qingfeng Lan · 2021
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Variational quantum algorithms
Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, and Patrick J. Coles · 2021
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Theeraphot Sriarunothai, Sabine Wölk, Gouri Shankar Giri, Nicolai Friis, Vedran Dunjko, Hans J. Briegel, and Christof Wunderlich · 2018
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Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii · 2018
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Effect of Data Encoding on the Expressive Power of Variational Quantum-Machine-Learning Models
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TensorFlow Quantum: A Software Framework for Quantum Machine Learning, 2021
Michael Broughton, Guillaume Verdon, Trevor McCourt, Antonio J. Martinez, Jae Hyeon Yoo, Sergei V. Isakov, Philip Massey, Ramin Halavati, Murphy Yuezhen Niu, Alexander Zlokapa, Evan Peters, Owen Lockwood, Andrea Skolik, Sofiene Jerbi, Vedran Dunjko, Martin Leib, Michael Streif, David Von Dollen, Hongxiang Chen, Shuxiang Cao, Roeland Wiersema, Hsin-Yuan Huang, Jarrod R. McClean, Ryan Babbush, Sergio Boixo, Dave Bacon, Alan K. Ho, Hartmut Neven, and Masoud Mohseni · 2021
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Training variational quantum algorithms is np-hard
Lennart Bittel and Martin Kliesch · 2021
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