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In recent years, the interest in leveraging quantum effects for enhancing machine learning tasks has significantly increased.
A. Dvoretzky et al
1956
Earlier work this paper cites.
C. J. Watkins and P. Dayan, “Q-learning,” Machine learning
1992
Earlier work this paper cites.
P. Dayan and T. J. Sejnowski, “TD( λ \lambda ) converges with probability 1,” Machine Learning
1994
Earlier work this paper cites.
T. Jaakkola, M. I. Jordan, and S. P. Singh, “Convergence of stochastic iterative dynamic programming algorithms,” in Advances in neural information processing systems
1994
Earlier work this paper cites.
C. H. Bennett and D. P. DiVincenzo, “Towards an engineering era?,” Nature
1995
Earlier work this paper cites.
Cambridge: Cambridge University Press, 2000
M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information · 2000
Earlier work this paper cites.
S. Singh, T. Jaakkola, M. L. Littman, and C. Szepesvári, “Convergence results for single-step on-policy reinforcement-learning algorithms,” Machine learning
2000
Earlier work this paper cites.
H. J. Briegel and G. D. las Cuevas, “Projective simulation for artificial intelligence,” Sci. Rep
2012
Earlier work this paper cites.
H. J. Briegel, “On creative machines and the physical origins of freedom,” Sci. Rep
2012
Earlier work this paper cites.
M. Schuld, I. Sinayskiy, and F. Petruccione, “The quest for a quantum neural network,” Quantum Information Processing
2014
Cited alongside, same era.
G. Paparo, V. Dunjko, A. Makmal, M. A. Martin-Delgado, and H. J. Briegel, “Quantum speed-up for active learning agents,” Phys. Rev. X
2014
Cited alongside, same era.
J. Mautner, A. Makmal, D. Manzano, M. Tiersch, and H. J. Briegel, “Projective Simulation for Classical Learning Agents: A Comprehensive Investigation,” New Gener. Comput
2015
Cited alongside, same era.
J. Biamonte, P. Wittek, N. Pancotti, P. R. N., Wiebe, and S. Lloyd, “Quantum machine learning,” vol. 549, 11 2016
2016
Cited alongside, same era.
S. Hangl, E. Ugur, S. Szedmak, and J. Piater, “Robotic playing for hierarchical complex skill learning,” in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst
2016
Cited alongside, same era.
V. Dunjko and H. Briegel, “Machine learning & artificial intelligence in the quantum domain: a review of recent progress,” Reports on Progress in Physics
2018
Later among the works it cites.
T. Sriarunothai, S. Wölk, G. S. Giri, N. Friis, V. Dunjko, H. J. Briegel, and C. Wunderlich, “Speeding-up the decision making of a learning agent using an ion trap quantum processor,” Quantum Science and Technology
2018
Later among the works it cites.
A. A. Melnikov, H. Poulsen Nautrup, M. Krenn, V. Dunjko, M. Tiersch, A. Zeilinger, and H. J. Briegel, “Active learning machine learns to create new quantum experiments,” Proc. Natl. Acad. Sci. U.S.A
2018
Later among the works it cites.
A. A. Melnikov, A. Makmal, and H. J. Briegel, “Benchmarking Projective Simulation in Navigation Problems,” IEEE Access
2018
Later among the works it cites.
Cambridge, MA: MIT Press, second ed., 2018
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A. Makmal, A. A. Melnikov, V. Dunjko, and H. J. Briegel, “Meta-learning within Projective Simulation,” IEEE Access
2016
Cited alongside, same era.
V. Dunjko, J. M. Taylor, and H. J. Briegel, “Quantum-enhanced machine learning,” Phys. Rev. Lett
2016
Cited alongside, same era.
A. A. Melnikov, A. Makmal, V. Dunjko, and H. J. Briegel, “Projective simulation with generalization,” Sci. Rep
2017
Cited alongside, same era.
R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction · 2018
Later among the works it cites.
J. Clausen and H. J. Briegel, “Quantum machine learning with glow for episodic tasks and decision games,” Phys. Rev. A
2018
Later among the works it cites.
H. P. Nautrup, N. Delfosse, V. Dunjko, H. J. Briegel, and N. Friis, “Optimizing Quantum Error Correction Codes with Reinforcement Learning,” Quantum
2019
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S. Hangl, V. Dunjko, H. J. Briegel, and J. Piater, “Skill learning by autonomous robotic playing using active learning and exploratory behavior composition,” Frontiers in Robotics and AI
2020
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