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* [[Kei Takada]], [[Hiroyuki Iizuka]], [[Masahito Yamamoto]] ('''2017'''). ''Reinforcement Learning for Creating Evaluation Function Using Convolutional Neural Network in Hex''. [[TAAI 2017]] » [[Hex]], [[Neural Networks#Convolutional|CNN]]
* [[Ari Weinstein]], [[Matthew Botvinick]] ('''2017'''). ''Structure Learning in Motor Control: A Deep Reinforcement Learning Model''. [https://arxiv.org/abs/1706.06827 arXiv:1706.06827]
* [[Takuya Hiraoka]], [https://dblp.org/pers/hd/t/Tsuchida:Masaaki Masaaki Tsuchida], [https://dblp.org/pers/hd/w/Watanabe:Yotaro Yotaro Watanabe] ('''2017'''). ''Deep Reinforcement Learning for Inquiry Dialog Policies with Logical Formula Embeddings''. [https://arxiv.org/abs/1708.00667 arXiv:1708.00667]
* [[William Uther]] ('''2017'''). ''[https://link.springer.com/referenceworkentry/10.1007/978-1-4899-7687-1_512 Markov Decision Processes]''. in [https://en.wikipedia.org/wiki/Claude_Sammut Claude Sammut], [https://en.wikipedia.org/wiki/Geoff_Webb Geoffrey I. Webb] (eds) ('''2017'''). ''[https://link.springer.com/referencework/10.1007%2F978-1-4899-7687-1 Encyclopedia of Machine Learning and Data Mining]''. [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
* [https://scholar.google.com/citations?user=zLksndkAAAAJ&hl=en Jayvant Anantpur], [https://dblp.org/pid/09/10702.html Nagendra Gulur Dwarakanath], [https://dblp.org/pid/16/4410.html Shivaram Kalyanakrishnan], [[Shalabh Bhatnagar]], [https://dblp.org/pid/45/3592.html R. Govindarajan] ('''2017'''). ''RLWS: A Reinforcement Learning based GPU Warp Scheduler''. [https://arxiv.org/abs/1712.04303 arXiv:1712.04303]
'''2018'''
* [[Hui Wang]], [[Michael Emmerich]], [[Aske Plaat]] ('''2018'''). ''Monte Carlo Q-learning for General Game Playing''. [https://arxiv.org/abs/1802.05944 arXiv:1802.05944] » [[Monte-Carlo Tree Search|MCTS]], [[General Game Playing]]
'''2019'''
* [https://scholar.google.co.uk/citations?user=OAkRr-YAAAAJ&hl=en Sanjeevan Ahilan], [[Peter Dayan]] ('''2019'''). ''Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning''. [https://arxiv.org/abs/1901.08492 arXiv:1901.08492]
* [https://scholar.google.co.in/citations?user=1QlrvHkAAAAJ&hl=en Chandramouli Kamanchi], [https://scholar.google.co.in/citations?user=nx4NlpsAAAAJ&hl=en Raghuram Bharadwaj Diddigi], [[Shalabh Bhatnagar]] ('''2019'''). ''Successive Over Relaxation Q-Learning''. [https://arxiv.org/abs/1903.03812 arXiv:1903.03812]
* [https://scholar.google.co.in/citations?user=1QlrvHkAAAAJ&hl=en Chandramouli Kamanchi], [https://scholar.google.co.in/citations?user=nx4NlpsAAAAJ&hl=en Raghuram Bharadwaj Diddigi], [[Shalabh Bhatnagar]] ('''2019'''). ''Second Order Value Iteration in Reinforcement Learning''. [https://arxiv.org/abs/1905.03927 arXiv:1905.03927]
* [[Marc Lanctot]], [[Edward Lockhart]], [[Jean-Baptiste Lespiau]], [[Vinicius Zambaldi]], [[Satyaki Upadhyay]], [[Julien Pérolat]], [[Sriram Srinivasan]], [[Finbarr Timbers]], [[Karl Tuyls]], [[Shayegan Omidshafiei]], [[Daniel Hennes]], [[Dustin Morrill]], [[Paul Muller]], [[Timo Ewalds]], [[Ryan Faulkner]], [[János Kramár]], [[Bart De Vylder]], [[Brennan Saeta]], [[James Bradbury]], [[David Ding]], [[Sebastian Borgeaud]], [[Matthew Lai]], [[Julian Schrittwieser]], [[Thomas Anthony]], [[Edward Hughes]], [[Ivo Danihelka]], [[Jonah Ryan-Davis]] ('''2019'''). ''OpenSpiel: A Framework for Reinforcement Learning in Games''. [https://arxiv.org/abs/1908.09453 arXiv:1908.09453] <ref>[https://github.com/deepmind/open_spiel/blob/master/docs/contributing.md open_spiel/contributing.md at master · deepmind/open_spiel · GitHub]</ref>
* [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Thomas Hubert]], [[Karen Simonyan]], [[Laurent Sifre]], [[Simon Schmitt]], [[Arthur Guez]], [[Edward Lockhart]], [[Demis Hassabis]], [[Thore Graepel]], [[Timothy Lillicrap]], [[David Silver]] ('''2019'''). ''Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model''. [https://arxiv.org/abs/1911.08265 arXiv:1911.08265] <ref>[http://www.talkchess.com/forum3/viewtopic.php?f=2&t=72381 New DeepMind paper] by GregNeto, [[CCC]], November 21, 2019</ref>
==2020 ...==
* [[Hung Guei]], [[Ting-Han Wei]], [[I-Chen Wu]] ('''2020'''). ''2048-like games for teaching reinforcement learning''. [[ICGA Journal#42_1|ICGA Journal, Vol. 42, No. 1]]
* [https://dblp.org/pid/233/8144.html Indu John], [https://scholar.google.co.in/citations?user=1QlrvHkAAAAJ&hl=en Chandramouli Kamanchi], [[Shalabh Bhatnagar]] ('''2020'''). ''Generalized Speedy Q-Learning''. [[IEEE#CSL|IEEE Control Systems Letters]], Vol. 4, No. 3, [https://arxiv.org/abs/1911.00397 arXiv:1911.00397]
* [[Takuya Hiraoka]], [https://dblp.org/pers/hd/i/Imagawa:Takahisa Takahisa Imagawa], [https://dblp.org/pers/hd/t/Tangkaratt:Voot Voot Tangkaratt], [https://dblp.org/pers/hd/o/Osa:Takayuki Takayuki Osa], [https://dblp.org/pers/hd/o/Onishi:Takashi Takashi Onishi], [https://dblp.org/pers/hd/t/Tsuruoka:Yoshimasa Yoshimasa Tsuruoka] ('''2020'''). ''Meta-Model-Based Meta-Policy Optimization''. [https://arxiv.org/abs/2006.02608 arXiv:2006.02608]
=Postings=
