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* [[Aston Zhang]], [[Zack C. Lipton]], [[Mu Li]], [[Alex J. Smola]] ('''2019'''). ''[https://www.d2l.ai/index.html Dive into Deep Learning]''. An interactive deep learning book with code, math, and discussions
* [[Johannes Czech]] ('''2019'''). ''Deep Reinforcement Learning for Crazyhouse''. Master thesis, [[Darmstadt University of Technology|TU Darmstadt]], [https://ml-research.github.io/papers/czech2019deep.pdf pdf] » [[CrazyAra]]
* [[Hsiao-Chung Hsieh]], [[Ti-Rong Wu]], [[Ting-Han Wei]], [[I-Chen Wu]] ('''2019'''). ''Net2Net Extension for the AlphaGo Zero Algorithm''. [[Advances in Computer Games 16]]
* [[Tomihiro Kimura]], [[Kokolo Ikeda]] ('''2019'''). ''Designing Policy Network with Deep Learning in Turn-Based Strategy Games''. [[Advances in Computer Games 16]]
==2020 ...==
* [[Garrett Bingham]], [[William Macke]], [[Risto Miikkulainen]] ('''2020'''). ''Evolutionary Optimization of Deep Learning Activation Functions''. [https://arxiv.org/abs/2002.07224 arXiv:2002.07224]
* [[Jason Liang]], [[Santiago Gonzalez]], [[Risto Miikkulainen]] ('''2020'''). ''Population-Based Training for Loss Function Optimization''. [https://arxiv.org/abs/2002.04225 arXiv:2002.04225]
* [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Thomas Hubert]], [[Karen Simonyan]], [[Laurent Sifre]], [[Simon Schmitt]], [[Arthur Guez]], [[Edward Lockhart]], [[Demis Hassabis]], [[Thore Graepel]], [[Timothy Lillicrap]], [[David Silver]] ('''2020'''). ''[https://www.nature.com/articles/s41586-020-03051-4 Mastering Atari, Go, chess and shogi by planning with a learned model]''. [https://en.wikipedia.org/wiki/Nature_%28journal%29 Nature], Vol. 588 <ref>[https://deepmind.com/blog/article/muzero-mastering-go-chess-shogi-and-atari-without-rules?fbclid=IwAR3mSwrn1YXDKr9uuGm2GlFKh76wBilex7f8QvBiQecwiVmAvD6Bkyjx-rE MuZero: Mastering Go, chess, shogi and Atari without rules]</ref> <ref>[https://github.com/koulanurag/muzero-pytorch GitHub - koulanurag/muzero-pytorch: Pytorch Implementation of MuZero]</ref>
* [[Reid McIlroy-Young]], [[Siddhartha Sen]], [[Jon Kleinberg]], [[Ashton Anderson]] ('''2020'''). ''Aligning Superhuman AI with Human Behavior: Chess as a Model System''. In Proceedings of the 26th [[ACM#SIGKDD|ACM SIGKDD 2020]], [https://arxiv.org/abs/2006.01855 arXiv:2006.01855] » [[Maia Chess]]
* [[Reid McIlroy-Young]], [[Russell Wang]], [[Siddhartha Sen]], [[Jon Kleinberg]], [[Ashton Anderson]] ('''2020'''). ''Learning Personalized Models of Human Behavior in Chess''. [https://arxiv.org/abs/2008.10086 arXiv:2008.10086]
* [[Maximilian Alexander Gehrke]] ('''2021'''). ''Assessing Popular Chess Variants Using Deep Reinforcement Learning''. Master thesis, [[Darmstadt University of Technology|TU Darmstadt]], [https://ml-research.github.io/papers/gehrke2021assessing.pdf pdf] » [[CrazyAra]]
* [[Dominik Klein]] ('''2021'''). ''[https://github.com/asdfjkl/neural_network_chess Neural Networks For Chess]''. [https://github.com/asdfjkl/neural_network_chess/releases/tag/v1.1 Release Version 1.1 · GitHub] <ref>[https://www.talkchess.com/forum3/viewtopic.php?f=2&t=78283 Book about Neural Networks for Chess] by dkl, [[CCC]], September 29, 2021</ref>
* [[Thomas McGrath]], [[Andrei Kapishnikov]], [[Nenad Tomašev]], [[Adam Pearce]], [[Demis Hassabis]], [[Been Kim]], [[Ulrich Paquet]], [[Vladimir Kramnik]] ('''2021'''). ''Acquisition of Chess Knowledge in AlphaZero''. [https://arxiv.org/abs/2111.09259 arXiv:2111.09259] <ref>[https://en.chessbase.com/post/acquisition-of-chess-knowledge-in-alphazero Acquisition of Chess Knowledge in AlphaZero], [[ChessBase|ChessBase News]], November 18, 2021</ref>
* [[Tristan Cazenave]], [[Julien Sentuc]], [[Mathurin Videau]] ('''2021'''). ''Cosine Annealing, Mixnet and Swish Activation for Computer Go''. [[Advances in Computer Games 17]]
* [[Hung-Jui Chang]], [[Cheng Yueh]], [[Gang-Yu Fan]], [[Ting-Yu Lin]], [[Tsan-sheng Hsu]] ('''2021'''). ''Opponent Model Selection Using Deep Learning''. [[Advances in Computer Games 17]]
* [[Rejwana Haque]], [[Ting Han Wei]], [[Martin Müller]] ('''2021'''). ''On the Road to Perfection? Evaluating Leela Chess Zero Against Endgame Tablebases''. [[Advances in Computer Games 17]]
* [[Boris Doux]], [[Benjamin Negrevergne]], [[Tristan Cazenave]] ('''2021'''). ''Deep Reinforcement Learning for Morpion Solitaire''. [[Advances in Computer Games 17]]
* [[Aðalsteinn Pálsson]], [[Yngvi Björnsson]] ('''2021'''). ''Evaluating Interpretability Methods for DNNs in Game-Playing Agents''. [[Advances in Computer Games 17]]
* [[Dennis Soemers]], [[Vegard Mella]], [[Cameron Browne]], [[Olivier Teytaud]] ('''2021'''). ''Deep learning for general game playing with Ludii and Polygames''. [[ICGA Journal#43_3|ICGA Journal, Vol. 43, No. 3]]
=Forum Posts=
* [https://github.com/gcp/leela-zero GitHub - gcp/leela-zero: Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper] by [[Gian-Carlo Pascutto]] et al. » [[Leela Zero]]
* [https://medium.com/applied-data-science/how-to-build-your-own-alphazero-ai-using-python-and-keras-7f664945c188 How to build your own AlphaZero AI using Python and Keras] by [https://www.linkedin.com/in/davidtfoster/ David Foster], January 26, 2018 » [[AlphaZero]], [[Connect Four]], [[Python]] <ref>[http://www.talkchess.com/forum/viewtopic.php?t=66443 Connect 4 AlphaZero implemented using Python...] by [[Steve Maughan]], [[CCC]], January 29, 2018</ref>
* [https://ai.facebook.com/blog/open-sourcing-polygames-a-new-framework-for-training-ai-bots-through-self-play/ Open-sourcing Polygames, a new framework for training AI bots through self-play]
* [https://github.com/facebookarchive/Polygames GitHub - facebookarchive/Polygames: The project is a platform of zero learning with a library of games]
===Music Generation===
* [http://www.asimovinstitute.org/analyzing-deep-learning-tools-music/ Analyzing Six Deep Learning Tools for Music Generation] by [http://www.asimovinstitute.org/team/ Frank Brinkkemper], [http://www.asimovinstitute.org/ The Asimov Institute], October 5, 2016
==Videos==
* [https://www.youtube.com/channel/UC9OeZkIwhzfv-_Cb7fCikLQ Deep Learning SIMPLIFIED: The Series Intro] [https://en.wikipedia.org/wiki/YouTube YouTube] Videos
* <span id="SchmidhuberVideoDeepLearning"></span>[https://www.youtube.com/watch?v=6bOMf9zr7N8 Deep Learning RNNaissance] with [[Jürgen Schmidhuber]], [https://en.wikipedia.org/wiki/YouTube YouTube] Video
: {{#evu:https://www.youtube.com/watch?v=6bOMf9zr7N8|alignment=left|valignment=top}}
