Reinforcement Learning For Sorting
Reinforcement Learning for Sorting is a computational framework within automated sorting that employs reinforcement learning to optimize sorting strategies by enabling an agent to learn sequential decision policies through interaction with an environment to maximize cumulative reward based on sorting efficiency.
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407
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56
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8
Institutions
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2017–2026
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Faster sorting algorithms discovered using deep reinforcement learning
Daniel J. Mankowitz, Andrea Michi, Anton Zhernov et al. · Nature · 2023 · 161 citations · Full text
Algorithm Selection using Reinforcement Learning
Michail G. Lagoudakis, Michael L. Littman · 2000 · 135 citations
Strong Generalization and Efficiency in Neural Programs
Yujia Li, Felix Gimeno, Pushmeet Kohli et al. · arXiv (Cornell University) · 2020 · 19 citations · Full text
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Google DeepMind (United Kingdom)
London, United Kingdom
2 h-index
31 publications
4.7K citations
German University in Cairo
Cairo, Egypt
1 h-index
5 publications
115 citations
AT&T (United States)
Bedminster, United States
1 h-index
1 publications
135 citations
Duke University
Durham, United States
1 h-index
1 publications
135 citations
Medizinische Hochschule Hannover
Hanover, Germany
1 h-index
2 publications
66 citations

University of Wisconsin System
Madison, United States
1 h-index
1 publications
13 citations
KU Leuven
Leuven, Belgium
1 h-index
1 publications
33 citations
Google (United States)
Mountain View, United States
1 h-index
1 publications
161 citations
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Repository · 2 publications · 32 citations
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Repository · 1 publications · 10 citations
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1 publications · 23 citations
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1 publications · 161 citations
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1 publications · 13 citations
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