Fetching the paper…
Reading the bibliography…
Quantum reinforcement learning (QRL) is a promising paradigm for near-term quantum devices.
Machine learning meets quantum physics
Sankar Das Sarma, Dong-Ling Deng, and Lu-Ming Duan · 1945
Earlier work this paper cites.
Learning from delayed rewards
Christopher J. C. H. Watkins · 1989
Earlier work this paper cites.
Q-learning
Christopher J. C. H. Watkins and Peter Dayan · 1992
Earlier work this paper cites.
Reinforcement Learning for Robots Using Neural Networks
Long-Ji Lin · 1992
Earlier work this paper cites.
Algorithms for quantum computation: discrete logarithms and factoring
Peter W Shor · 1994
Earlier work this paper cites.
On-line q-learning using connectionist systems
Gavin A Rummery and Mahesan Niranjan · 1994
Earlier work this paper cites.
Quantum mechanics helps in searching for a needle in a haystack
Lov Kumar Grover · 1997
Earlier work this paper cites.
Quantum algorithm providing exponential speed increase for finding eigenvalues and eigenvectors
Daniel S. Abrams and Seth Lloyd · 1999
Earlier work this paper cites.
Reinforcement learning in continuous time and space
Kenji Doya · 2000
Earlier work this paper cites.
A natural policy gradient
Sham M Kakade · 2001
Earlier work this paper cites.
Quantum np-a survey
Dorit Aharonov and Tomer Naveh · 2002
Earlier work this paper cites.
Optimal control of coupled spin dynamics: design of nmr pulse sequences by gradient ascent algorithms
Navin Khaneja, Timo Reiss, Cindie Kehlet, Thomas Schulte-Herbrüggen, and Steffen J. Glaser · 2004
Earlier work this paper cites.
The complexity of the local hamiltonian problem
Julia Kempe, Alexei Kitaev, and Oded Regev · 2006
Earlier work this paper cites.
Quantum reinforcement learning
Daoyi Dong, Chunlin Chen, Hanxiong Li, and Tzyh-Jong Tarn · 2008
Earlier work this paper cites.
Quantum hamiltonian complexity
Sevag Gharibian, Yichen Huang, Zeph Landau, and Seung Woo Shin · 2009
Earlier work this paper cites.
Quantum Computation and Quantum Information
Michael A. Nielsen and Isaac L. Chuang · 2011
Earlier work this paper cites.
Quantum algorithm for data fitting
Nathan Wiebe, Daniel Braun, and Seth Lloyd · 2012
Earlier work this paper cites.
Reinforcement learning and markov decision processes
Martijn Van Otterlo and Marco Wiering · 2012
Earlier work this paper cites.
Playing atari with deep reinforcement learning
Mnih Volodymyr, Kavukcuoglu Koray, Silver David, Graves Alex, Antonoglou Ioannis, Wierstra Daan, and Riedmiller Martin · 2013
Earlier work this paper cites.
Quantum support vector machine for big data classification
Patrick Rebentrost, Masoud Mohseni, and Seth Lloyd · 2014
Earlier work this paper cites.
Quantum principal component analysis
Seth Lloyd, Masoud Mohseni, and Patrick Rebentrost · 2014
Earlier work this paper cites.
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
Cited alongside, same era.
Human-level control through deep reinforcement learning
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
Cited alongside, same era.
Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2015
Cited alongside, same era.
Quantum-enhanced deliberation of learning agents using trapped ions
V Dunjko, N Friis, and H J Briegel · 2015
Cited alongside, same era.
Universal quantum control through deep reinforcement learning
Murphy Yuezhen Niu, Sergio Boixo, Vadim N Smelyanskiy, and Hartmut Neven · 2019
Later among the works it cites.
Generalizable control for quantum parameter estimation through reinforcement learning
Han Xu, Junning Li, Liqiang Liu, Yu Wang, Haidong Yuan, and Xin Wang · 2019
Later among the works it cites.
When does reinforcement learning stand out in quantum control? a comparative study on state preparation
Xiao-Ming Zhang, Zezhu Wei, Raza Asad, Xu-Chen Yang, and Xin Wang · 2019
Later among the works it cites.
Reinforcement learning for humanoid robotics
Jan Peters, Sethu Vijayakumar, and Stefan Schaal · 2020
Closest in time.
Reinforcement-learning-assisted quantum optimization
Matteo M. Wauters, Emanuele Panizon, Glen B. Mbeng, and Giuseppe E. Santoro · 2020
Closest in time.
Variational quantum circuits for deep reinforcement learning
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Diederik P Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, and Demis Hassabis · 2016
Cited alongside, same era.
Benchmarking deep reinforcement learning for continuous control
Yan Duan, Xi Chen, Rein Houthooft, John Schulman, and Pieter Abbeel · 2016
Cited alongside, same era.
Learning in quantum control: High-dimensional global optimization for noisy quantum dynamics
Pantita Palittapongarnpim, Peter Wittek, Ehsan Zahedinejad, Shakib Vedaie, and Barry C. Sanders · 2016
Cited alongside, same era.
Quantum-enhanced machine learning
Vedran Dunjko, Jacob M. Taylor, and Hans J. Briegel · 2016
Cited alongside, same era.
Reinforcement learning with parameterized actions
Warwick Masson, Pravesh Ranchod, and George Konidaris · 2016
Cited alongside, same era.
Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
Cited alongside, same era.
Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
Cited alongside, same era.
Samuel Yen-Chi Chen, Chao-Han Huck Yang, Jun Qi, Pin-Yu Chen, Xiaoli Ma, and Hsi-Sheng Goan · 2020
Closest in time.
Reinforcement learning with quantum variational circuits
Owen Lockwood and Mei Si · 2020
Closest in time.
Playing atari with hybrid quantum-classical reinforcement learning
Owen Lockwood and Mei Si · 2021
Closest in time.
Parametrized quantum policies for reinforcement learning
Sofiene Jerbi, Casper Gyurik, Simon Marshall, Hans Briegel, and Vedran Dunjko · 2021
Closest in time.
Experimental quantum speed-up in reinforcement learning agents
Valeria Saggio, Beate E Asenbeck, Arne Hamann, Teodor Strömberg, Peter Schiansky, Vedran Dunjko, Nicolai Friis, Nicholas C Harris, Michael Hochberg, Dirk Englund, et al · 2021
Closest in time.
Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, and Martin Roetteler · 2021
Closest in time.
Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning
Andrea Skolik, Sofiene Jerbi, and Vedran Dunjko · 2022
Closest in time.
Quantum Deep Q-Learning with Distributed Prioritized Experience Replay
Samuel Yen-Chi Chen · 2023
Closest in time.
Quantum Natural Policy Gradients: Towards Sample-Efficient Reinforcement Learning
Nico Meyer, Daniel D. Scherer, Axel Plinge, Christopher Mutschler, and Michael J. Hartmann · 2023
Closest in time.
Policy gradients using variational quantum circuits
André Sequeira, Luis Paulo Santos, and Luis Soares Barbosa · 2023
Closest in time.
Quantum reinforcement learning via policy iteration
El Amine Cherrat, Iordanis Kerenidis, and Anupam Prakash · 2023
Closest in time.
A survey on quantum reinforcement learning, 2024
Nico Meyer, Christian Ufrecht, Maniraman Periyasamy, Daniel D. Scherer, Axel Plinge, and Christopher Mutschler · 2024
Closest in time.
Projective simulation for artificial intelligence
Hans J. Briegel and Gemma De las Cuevas · 2045
Closest in time.
Projective simulation with generalization
Alexey A. Melnikov, Adi Makmal, Vedran Dunjko, and Hans J. Briegel · 2045
Closest in time.
Speeding-up the decision making of a learning agent using an ion trap quantum processor
Th Sriarunothai, S Wölk, G S Giri, N Friis, V Dunjko, H J Briegel, and Ch Wunderlich · 2058
Closest in time.
Parameterized quantum circuits as machine learning models
Marcello Benedetti, Erika Lloyd, Stefan Sack, and Mattia Fiorentini · 2058
Closest in time.