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* [[Gerald Tesauro]] ('''1992'''). ''[http://dl.acm.org/citation.cfm?id=139616 Practical Issues in Temporal Difference Learning]''. [https://en.wikipedia.org/wiki/Machine_Learning_(journal) Machine Learning], Vol. 8, No. 3-4
* [[Manuela Veloso]] ('''1992'''). ''[http://search.library.cmu.edu/vufind/Record/421096 Learning by Analogical Reasoning in General Purpose Problem Solving]''. Ph.D. thesis, [[Carnegie Mellon University]], advisor [[Jaime Carbonell]]
* [[Chris J. Thornton]] ('''1992'''). ''Techniques in Computational Learning: An Introduction''. [https://en.wikipedia.org/wiki/Chapman_%26_Hall Chapman & Hall]
'''1993'''
* [[Michael Gherrity]] ('''1993'''). ''A Game Learning Machine''. Ph.D. Thesis, [http://de.wikipedia.org/wiki/University_of_California,_San_Diego University of California, San Diego], [http://www.gherrity.org/thesis.ps.gz zipped ps]
* [[Jonathan Baxter]], [[Andrew Tridgell]], [[Lex Weaver]] ('''2000'''). ''Learning to Play Chess Using Temporal Differences''. [http://www.dblp.org/db/journals/ml/ml40.html#BaxterTW00 Machine Learning, Vol 40, No. 3], [http://www.cs.princeton.edu/courses/archive/fall06/cos402/papers/chess-RL.pdf pdf]
* [[Michael Bain]], [[Stephen Muggleton]], [[Ashwin Srinivasan]] ('''2000'''). ''Generalising Closed World Specialisation: A Chess End Game Application''. [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.24.3499 CitySeerX]
* [[Chris J. Thornton]] ('''2000'''). ''[https://www.goodreads.com/book/show/1097454.Truth_from_Trash Truth from Trash: How Learning Makes Sense]''. [https://en.wikipedia.org/wiki/MIT_Press Bradford Books] <ref>[[Jean Hayes Michie]] ('''2001'''). ''[https://www.aaai.org/ojs/index.php/aimagazine/article/view/1599/0 Machine Learning and Light Relief: A Review of Truth from Trash]''. [[AAAI#AIMAG|AI Magazine]], Vol. 22 No. 4, [http://www.aaai.org/ojs/index.php/aimagazine/article/download/1599/1498 pdf]</ref>
'''2001'''
* [[Nicol N. Schraudolph]], [[Peter Dayan]], [[Terrence J. Sejnowski]] ('''2001'''). ''[http://nic.schraudolph.org/bib2html/b2hd-SchDaySej01.html Learning to Evaluate Go Positions via Temporal Difference Methods]''. [http://jasss.soc.surrey.ac.uk/7/1/reviews/takama.html Computational Intelligence in Games, Studies in Fuzziness and Soft Computing] [http://www.springer.com/economics?SGWID=1-165-6-73481-0 Physica-Verlag], revised version of [[Nicol N. Schraudolph#1993|1993 paper]]
* [[Pedro Campos]], [[Thibault Langlois]] ('''2003'''). ''[http://ilk.uvt.nl/icga/journal/contents/content26-4.htm#ABALEARN Abalearn: a Program that Learns How to Play Abalone]''. [[ICGA Journal#26_4|ICGA Journal, Vol. 26, No. 4]]
* [[David Gleich]] ('''2003'''). ''Machine Learning in Computer Chess: Genetic Programming and KRK''. [https://en.wikipedia.org/wiki/Harvey_Mudd_College Harvey Mudd College], [http://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202003%20-%20Machine%20Learning%20in%20Computer%20Chess.pdf pdf]
* [[Henk Mannen]] ('''2003'''). ''Learning to play chess using reinforcement learning with database games''. Master’s thesis, [http://students.uu.nl/en/hum/cognitive-artificial-intelligence Cognitive Artificial Intelligence], [https://en.wikipedia.org/wiki/Utrecht_University Utrecht University], [https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.109.810&rep=rep1&type=pdf pdf]
* [[Jan Žižka]], [[Michal Mádr]] ('''2003'''). ''[https://www.muni.cz/research/publications/490371 Learning Representative Patterns from Real Chess Positions: A Case Study]''. [http://dblp.uni-trier.de/db/conf/iicai/iicai2003.html#ZizkaM03 IICAI 2003]
'''2004'''
* [[Daniel Osman]], [[Jacek Mańdziuk]] ('''2004'''). ''Comparison of TDLeaf and TD learning in Game Playing Domain''. [http://www.informatik.uni-trier.de/~ley/db/conf/iconip/iconip2004.html#OsmanM04 11. ICONIP], [http://www.mini.pw.edu.pl/~mandziuk/PRACE/ICONIP04.pdf pdf]
* [[Albert Xin Jiang]] ('''2004'''). ''Multiagent Reinforcement Learning in Stochastic Games with Continuous Action Spaces''. [http://www.cs.ubc.ca/%7Ejiang/papers/continuous.pdf pdf]
* [[Henk Mannen]], [[Marco Wiering]] ('''2004'''). ''[https://www.semanticscholar.org/paper/Learning-to-Play-Chess-using-TD(lambda)-learning-Mannen-Wiering/00a6f81c8ebe8408c147841f26ed27eb13fb07f3 Learning to play chess using TD(λ)-learning with database games]''. [http://students.uu.nl/en/hum/cognitive-artificial-intelligence Cognitive Artificial Intelligence], [https://en.wikipedia.org/wiki/Utrecht_University Utrecht University], Benelearn’04, [https://www.ai.rug.nl/~mwiering/GROUP/ARTICLES/learning-chess.pdf pdf]
==2005 ...==
* [[Dave Gomboc]], [[Michael Buro]], [[Tony Marsland]] ('''2005'''). ''Tuning evaluation functions by maximizing concordance'' Theoretical Computer Science, Volume 349, Issue 2, pp. 202-229, [http://www.cs.ualberta.ca/%7Emburo/ps/tcs-learn.pdf pdf]
* [[Matthia Sabatelli]], [[Francesco Bidoia]], [[Valeriu Codreanu]], [[Marco Wiering]] ('''2018'''). ''Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead''. ICPRAM 2018, [http://www.ai.rug.nl/~mwiering/GROUP/ARTICLES/ICPRAM_CHESS_DNN_2018.pdf pdf]
* [[Takeshi Ito]] ('''2018'''). ''Game learning support system based on future position''. [[CG 2018]], [[ICGA Journal#40_4|ICGA Journal, Vol. 40, No. 4]]
* [[Kristian Kersting]] ('''2018'''). ''[https://www.frontiersin.org/articles/10.3389/fdata.2018.00006/full Machine Learning and Artificial Intelligence: Two Fellow Travelers on the Quest for Intelligent Behavior in Machines]''. [https://www.frontiersin.org/journals/big-data# Frontiers in Big Data]
'''2019'''
* [[Herilalaina Rakotoarison]], [[Marc Schoenauer]], [[Michèle Sebag]] ('''2019'''). ''Automated Machine Learning with Monte-Carlo Tree Search''. [https://arxiv.org/abs/1906.00170 arXiv:1906.00170]
* [[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 ...==
* [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Thomas Hubert]], [[Karen Simonyan]], [[Laurent Sifre]], [[Simon Schmitt]], [[Arthur Guez]], [[Edward LockharLockhart]], [[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>* [[Johannes Czech]], [[Moritz Willig]], [[Alena Beyer]], [[Kristian Kersting]], [[Johannes Fürnkranz]] ('''2020'''). ''[https://www.frontiersin.org/articles/10.3389/frai.2020.00024/full Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data]''. [https://www.frontiersin.org/journals/artificial-intelligence# Frontiers in Artificial Intelligence] » [[CrazyAra]]
=Forum Posts=
