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We introduce the reinforcement quantum annealing (RQA) scheme in which an intelligent agent interacts with a quantum annealer that plays the stochastic environment role of learning automata and tries to iteratively find better Ising Hamiltonians for the given problem of interest.
Where the really hard problems are
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Ohzeki, M. & Nishimori, H · 2011
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Finding low-energy conformations of lattice protein models by quantum annealing
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Narendra, K. S. & Thathachar, M. A · 2012
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The strategy challenge in smt solving
De Moura, L. & Passmore, G. O · 2013
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Discrete optimization using quantum annealing on sparse ising models
Bian, Z. et al · 2014
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A practical heuristic for finding graph minors
Cai, J., Macready, W. G. & Roy, A · 2014
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A case study in programming a quantum annealer for hard operational planning problems
Rieffel, E. G. et al · 2015
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Quantum annealing implementation of job-shop scheduling
Venturelli, D., Marchand, D. J. & Rojo, G · 2015
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Perdomo-Ortiz, A., Fluegemann, J., Narasimhan, S., Biswas, R. & Smelyanskiy, V. N · 2015
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Application of quantum annealing to training of deep neural networks
Adachi, S. H. & Henderson, M. P · 2015
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Quantum annealing correction for random ising problems
Pudenz, K. L., Albash, T. & Lidar, D. A · 2015
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Tran, T. T. et al · 2016
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A method of finding a lower energy solution to a qubo/ising objective function
Dorband, J. E · 2018
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Simple constraint embedding for quantum annealers
Vyskocil, T. & Djidjev, H · 2018
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Reinforcement learning: An introduction (MIT press, 2018)
Sutton, R. S. & Barto, A. G · 2018
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Integer factoring algorithms
Balasubramanian, K. & Abbas, A. M · 2018
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Enhancing the efficiency of quantum annealing via reinforcement: A path-integral monte carlo simulation of the quantum reinforcement algorithm
Ramezanpour, A · 2018
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An SAT-based quantum programming paradigm
Ayanzadeh, R., Halem, M. & Finin, T · 2019
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Biamonte, J. et al · 2017
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Optimizing the spin reversal transform on the d-wave 2000q
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Mapping np-hard problems to restricted adiabatic quantum architectures
Mooney, G. J., Tonetto, S. U., Hill, C. D. & Hollenberg, L. C · 2019
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Embedding inequality constraints for quantum annealing optimization
Vyskočil, T., Pakin, S. & Djidjev, H. N · 2019
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A survey on compressive sensing: Classical results and recent advancements
Mousavi, S., Taghiabadi, M. M. R. & Ayanzadeh, R · 2019
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Ayanzadeh, R., Halem, M. & Finin, T · 2019
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Clausal form transformation in maxsat
Li, C. M., Manyà, F. & Soler, J. R · 2019
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Pre-and post-processing in quantum-computational hydrologic inverse analysis
Golden, J. K. & O’Malley, D · 2019
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Quantum-assisted greedy algorithms
Ayanzadeh, R., Halem, M., Dorband, J. & Finin, T · 2019
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