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=Learning Paradigms=
There are three major learning [https://en.wikipedia.org/wiki/Paradigm paradigms], each corresponding to a particular abstract learning task. These are [https://en.wikipedia.org/wiki/Supervised_learning [Supervised Learning|supervised learning]], [https://en.wikipedia.org/wiki/Unsupervised_learning unsupervised learning] and [[Reinforcement Learning|reinforcement learning]]. Usually any given type of [[Neural Networks|neural network]] architecture can be employed in any of those tasks.
==Supervised Learning==
''see main page [[Supervised Learning]]''
Supervised learning is learning from examples provided by a knowledgable external supervisor. In machine learning, supervised learning is a technique for deducing a function from training data. The training data consist of pairs of input objects and desired outputs, f.i. in computer chess a sequence of positions associated with the outcome of a game <ref>[http://www.aihorizon.com/essays/generalai/supervised_unsupervised_machine_learning.htm AI Horizon: Machine Learning, Part II: Supervised and Unsupervised Learning]</ref> .
* [[Planning]]
* [[Reinforcement Learning]]
* [[Supervised Learning]]
* [[Temporal Difference Learning]]
<span id="Programs"></span>
=Programs=
* [[Allie]]
* [[AlphaZero]]
* [[Alexs]]
* [[Tempo (engine)|Tempo]]
* [[Winter]]
* [[Yace]]
=See also=
==1950 ...==
* [[Mathematician#SCKleene|Stephen C. Kleene]] ('''1951''') ''Representation of Events in Nerve Nets and Finite Automata''. RM-704, [https://en.wikipedia.org/wiki/RAND_Corporation RAND paper], [http://www.rand.org/content/dam/rand/pubs/research_memoranda/2008/RM704.pdf pdf], reprinted in
: [[Claude Shannon]], [[John McCarthy]] (eds.) ('''1956'''). ''Automata Studies''. [httphttps://presswww.princetonwikidata.eduorg/mathwiki/series/amh.html Q15763006 Annals of Mathematics Studies], No. 34
* [http://adsabs.harvard.edu/cgi-bin/nph-abs_connect?return_req=no_params&author=Richards,%20Paul%20I.&db_key=GEN Paul I. Richards] ('''1951'''). ''Machines which can learn''. [https://en.wikipedia.org/wiki/American_Scientist American Scientist], 39:711-716
* [http://adsabs.harvard.edu/cgi-bin/nph-abs_connect?return_req=no_params&author=Richards,%20Paul%20I.&db_key=GEN Paul I. Richards] ('''1952'''). ''On Game Learning Machines''. [https://en.wikipedia.org/wiki/The_Scientific_Monthly The Scientific Monthly], Vol. 74, No. 4, April 1952
* [[Marvin Minsky]] ('''1954'''). ''Neural Nets and the Brain Model Problem''. Ph.D. dissertation, [https://en.wikipedia.org/wiki/Princeton_University Princeton University]
==1955 ...==
* [[Mathematician#RRBush|Robert R. Bush]], [[Mathematician#Mosteller|Frederick Mosteller]] ('''1955'''). ''[https://psycnet.apa.org/record/1956-02349-000 Stochastic models for learning]''. [https://en.wikipedia.org/wiki/Wiley_(publisher) John Wiley & Sons]
* [[John von Neumann]] ('''1956'''). ''Probabilistic Logic and the Synthesis of Reliable Organisms From Unreliable Components''. in
: [[Claude Shannon]], [[John McCarthy]] (eds.) ('''1956'''). ''Automata Studies''. [http://press.princeton.edu/math/series/amh.html Annals of Mathematics Studies], No. 34, [http://www.dna.caltech.edu/courses/cs191/paperscs191/VonNeumann56.pdf pdf]
* [[Mathematician#Mosteller|Frederick Mosteller]] ('''1956'''). ''Stochastic Learning Models''. in [[Mathematician#JNeyman|Jerzy Neyman]] ('''1956'''). ''[https://projecteuclid.org/euclid.bsmsp/1200511851 Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, Volume 5: Contributions to Econometrics, Industrial Research, and Psychometry]'', [https://pdfs.semanticscholar.org/4df2/038d7edee92e9fbd302b42cccee7b28f96ce.pdf pdf]
* [https://en.wikipedia.org/wiki/Frank_Rosenblatt Frank Rosenblatt] ('''1957'''). ''The Perceptron - a Perceiving and Recognizing Automaton''. Report 85-460-1, Cornell Aeronautical Laboratory <ref>[http://csis.pace.edu/~ctappert/srd2011/rosenblatt-contributions.htm Rosenblatt's Contributions]</ref>
* [http://www.purbeckradar.org.uk/biography/uttley_albert_m.htm Albert M. Uttley] ('''1959'''). ''[http://rmp.aps.org/abstract/RMP/v31/i2/p546_1 Imitation of Pattern Recognition and Trial-and-error Learning in a Conditional Probability Computer]''. [https://en.wikipedia.org/wiki/Reviews_of_Modern_Physics Reviews of Modern Physics], Vol. 31, April 1959, pp. 546-548 <ref>[https://en.wikipedia.org/wiki/Ratio_Club Ratio Club from Wikipedia]</ref> <ref>[https://en.wikipedia.org/wiki/Royal_Radar_Establishment Royal Radar Establishment from Wikipedia]</ref>
* [[Jacques Pitrat]] ('''1976'''). ''Realization of a Program Learning to Find Combinations at Chess.'' Computer Oriented Learning Processes (ed. J. Simon). Noordhoff, Groningen, The Netherlands.
* [[Pericles Negri]] ('''1977'''). ''Inductive Learning in a Hierarchical Model for Representing Knowledge in Chess End Games''. [http://www.mli.gmu.edu/papers/69-78/77-2.pdf pdf]
* [[Ryszard Michalski]], [[Pericles Negri]] ('''1977'''). ''An experiment on inductive learning in chess endgames''. [httphttps://www.doc.ic.ac.uk/~shm/MI/mi8.html Machine Intelligence 8], [http://www.mli.gmu.edu/papers/69-78/77-1.pdf pdf]
* [[Boris Stilman]] ('''1977'''). ''The Computer Learns''. in ''1976 US Computer Chess Championship'', by [[David Levy]], Computer Science Press, Woodland Hills, CA, pp. 83-90
* [[Richard Sutton]] ('''1978'''). ''Single channel theory: A neuronal theory of learning''. Brain Theory Newsletter 3, No. 3/4, pp. 72-75.
* [[Alen Shapiro]], [[Tim Niblett]] ('''1982'''). ''Automatic Induction of Classification Rules for Chess End game.'' [[Advances in Computer Chess 3]]
* [[Thomas Nitsche]] ('''1982'''). ''A Learning Chess Program.'' [[Advances in Computer Chess 3]]
* [[Ryszard Michalski]], [[Jaime Carbonell]], [[Tom Mitchell]] ('''1983'''). ''[https://link.springer.com/book/10.1007%2F978-3-662-12405-5 Machine Learning: An Artificial Intelligence Approach]''. Tioga Publishing Company, ISBN 0-935382-05-4. [httphttps://booksen.googlewikipedia.comorg/wiki/books?id=KlNQAAAAMAAJ&q=isbn:0935382054&dq=isbn:0935382054&hl=de&ei=JE4-TtymDInUsgbmm_kG&sa=X&oi=book_result&ct=result&resnum=1&ved=0CCkQ6AEwAA google booksSpringer_Science%2BBusiness_Media Springer]
* [[Ross Quinlan]] ('''1983'''). ''Learning efficient classification procedures and their application to chess end games''. In Machine Learning: An Artificial Intelligence Approach, pages 463–482. Tioga, Palo Alto
* [[Alen Shapiro]] ('''1983'''). ''The Role of Structured Induction in Expert Systems''. [[University of Edinburgh]], Machine Intelligence Research Unit (Ph.D. thesis)
* [[Albrecht Heeffer]] ('''1985'''). ''Validating Concepts from Automated Acquisition Systems''. [[Conferences#IJCAI|IJCAI 85]], [http://ijcai.org/Past%20Proceedings/IJCAI-85-VOL1/PDF/118.pdf pdf]
* [[Hans Berliner]] ('''1985'''). ''Goals, Plans, and Mechanisms: Non-symbolically in an Evaluation Surface.'' Presentation at Evolution, Games, and Learning, Center for Nonlinear Studies, [[Los Alamos National Laboratory]], May 21.
* [[Ryszard Michalski]], [[Jaime Carbonell]], [[Tom Mitchell]] ('''1985, 2014'''). ''Machine [https://www.elsevier.com/books/machine-learning/michalski/978-0-08-051054-5?gclid=EAIaIQobChMItc_hsp_34AIVUeR3Ch2l9QcDEAYYASABEgKW4_D_BwEMachine Learning: An Artificial Intelligence Approach, Volume I]''. Morgan Kaufmann, ISBN 0-934613-09-5. [httphttps://booksen.googlewikipedia.comorg/wiki/books?id=TWzuUd5gsnkC&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google booksMorgan_Kaufmann_Publishers Morgan Kaufmann]* [[Igor Roizen]], [[Judea Pearl]] ('''1985'''). ''Learning Link Probabilities in Causal Trees.'' Proceedings of the Second Conference on [[Laveen Kanal#Uncertainty AI 1|Uncertainty in Artificial Intelligence1]]
'''1986'''
* [[Steven Skiena]] ('''1986'''). ''An Overview of Machine Learning in Chess.'' [[ICGA Journal#9_1|ICCA Journal, Vol. 9, No. 1]]
* [[Jens Christensen]], [[Richard Korf]] ('''1986'''). ''A Unified Theory of Heuristic Evaluation functions and Its Applications to Learning.'' Proceedings of the AAAI-86, pp. 148-152, [http://www.aaai.org/Papers/AAAI/1986/AAAI86-023.pdf pdf].* [[Ryszard Michalski]], [[Jaime Carbonell]], [[Tom Mitchell]] ('''1986'''). ''[https://dl.acm.org/citation.cfm?id=21934 Machine Learning: An Artificial Intelligence Approach, Volume II]''. Morgan Kaufmann, ISBN 0-934613-00-1. [httphttps://booksen.googlewikipedia.comorg/wiki/books?id=f9RylgKpHZsC&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google booksMorgan_Kaufmann_Publishers Morgan Kaufmann]* [[Tom Mitchell]], [[Jaime Carbonell]], [[Ryszard Michalski]] ('''1986'''). ''[httphttps://link.springer.com/book/10.1007/978%2F978-1-4613-2279-5 Machine Learning: A Guide to Current Research]''. [https://en.wikipedia.org/wiki/Wolters_Kluwer The Kluwer International Series in Engineering and Computer Science], Vol. 12
* [[Ivan Bratko]], [[Igor Kononenko]] ('''1986'''). ''Learning Rules from Incomplete and Noisy Data.'' Proceedings Unicom Seminar on the Scope of Artificial Intelligence in Statistics. Technical Press
'''1987'''
* [[Bruce Abramson]] ('''1988'''). ''Learning Expected-Outcome Evaluators in Chess.'' Proceedings of the 1988 AAAI Spring Symposium Series: Computer Game Playing, 26-28.
* [[Richard Sutton]] ('''1988'''). ''Learning to Predict by the Methods of Temporal Differences''. [https://en.wikipedia.org/wiki/Machine_Learning_%28journal%29 Machine Learning], Vol. 3, No. 1, [https://webdocs.cs.ualberta.ca/~sutton/papers/sutton-88-with-erratum.pdf pdf]
* [[David E. Goldberg]], [[Mathematician#Holland|John H. Holland]] ('''1988'''). ''[httphttps://wwwlink.springerlinkspringer.com/contentarticle/rw3572714v41q50710.1023/ A:1022602019183 Genetic Algorithms and Machine Learning]''. [https://enwww.wikipediaspringer.orgcom/wikijournal/Machine_Learning_%28journal%29 10994 Machine Learning], Vol. 3
* [[Mathematician#KADeJong|Kenneth A. De Jong]], [[Mathematician#ACSchultz|Alan C. Schultz]] ('''1988'''). ''Using Experience-Based Learning in Game Playing''. Proceedings of the Fifth International Machine Learning Conference, [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.52.5381 CiteSeerX] » [[Othello]]
* [[Kai-Fu Lee]], [[Sanjoy Mahajan]] ('''1988'''). ''[http://www.sciencedirect.com/science/article/pii/0004370288900768 A Pattern Classification Approach to Evaluation Function Learning]''. [https://en.wikipedia.org/wiki/Artificial_Intelligence_%28journal%29 Artificial Intelligence], Vol. 36, No. 1
* [[Paul E. Utgoff]] ('''1988'''). ''[http://dl.acm.org/citation.cfm?id=896712 ID5: An incremental ID3]''. [http://dblp.uni-trier.de/db/conf/icml/ml1988.html#Utgoff88 ML 1988]
'''1989'''
* [[David E. Goldberg]] ('''1989'''). ''Genetic Algorithms in Search, Optimization and Machine Learning''. [https://en.wikipedia.org/wiki/Addison-Wesley Addison-Wesley]
* [[Robert Levinson]] ('''1989'''). ''A Self-Learning, Pattern-Oriented Chess Program''. [[ICGA Journal#12_4|ICCA Journal, Vol. 12, No. 4]]
* [[Bruce Abramson]] ('''1989'''). ''On Learning and Testing Evaluation Functions.'' Proceedings of the Sixth Israeli Conference on Artificial Intelligence, 1989, 7-16.
* [[Bruce Abramson]] ('''1990'''). ''On Learning and Testing Evaluation Functions.'' Journal of Experimental and Theoretical Artificial Intelligence 2: 241-251.
* [[Tony Scherzer]], [[Linda Scherzer]], [[Dean Tjaden]] ('''1990'''). ''Learning in Bebe.'' [[Computers, Chess, and Cognition]] » [[Bebe#Award|Mephisto Best-Publication Award]]
* [[Yves Kodratoff]], [[Ryszard Michalski]] ('''1990, 2014'''). ''[https://www.elsevier.com/books/machine-learning/kodratoff/978-0-08-051055-2 Machine Learning: An Artificial Intelligence Approach, Volume III]''. Morgan Kaufmann, ISBN 1-55860-119-8. [httphttps://booksen.googlewikipedia.comorg/wiki/books?id=UDqCeuwVkkcC&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google booksMorgan_Kaufmann_Publishers Morgan Kaufmann]
* [[Michèle Sebag]] ('''1990'''). ''A symbolic-numerical approach for supervised learning from examples and rules''. Ph.D. thesis, [https://en.wikipedia.org/wiki/Paris_Dauphine_University Paris Dauphine University]
'''1991'''
* [[Robert Schapire]] ('''1991'''). ''The Design and Analysis of Efficient Learning Algorithms''. Ph.D. thesis, [[Massachusetts Institute of Technology]], supervisor [[Ronald L. Rivest]], [http://www.dtic.mil/dtic/tr/fulltext/u2/a231888.pdf pdf]
* [[Gerhard Mehlsam]], [[Hermann Kaindl]], [[Wilhelm Barth]] ('''1991'''). ''Feature Construction During Tree Learning''. [http://137.226.34.227/dblp/db/conf/ki/gwai91.html GWAI 1991]: 50-61.
* [[Alex van Tiggelen]] ('''1991'''). ''Neural Networks as a Guide to Optimization - The Chess Middle Game Explored''. [[ICGA Journal#14_3|ICCA Journal, Vol. 14, No. 3]]
* [[William Tunstall-Pedoe]] ('''1991'''). ''Genetic Algorithms Optimizing Evaluation Functions''. [[ICGA Journal#14_3|ICCA Journal, Vol. 14, No. 3]]
* [[Tony Scherzer]], [[Linda Scherzer]], [[Dean Tjaden]] ('''1991'''). ''Learning in Bebe.'' [[ICGA Journal#14_4|ICCA Journal, Vol. 14, No. 4]]
* [[Steven Walczak]] ('''1991'''). ''Predicting Actions from Induction on Past Performance''. Proceedings of the 8th International Workshop on Machine Learning , pp. 275-279. Morgan Kaufmann
* [[Paul E. Utgoff]], [[Jeffery A. Clouse]] ('''1991'''). ''[http://scholarworks.umass.edu/cs_faculty_pubs/193/ Two Kinds of Training Information for Evaluation Function Learning]''. [https://en.wikipedia.org/wiki/University_of_Massachusetts_Amherst University of Massachusetts, Amherst], Proceedings of the [[AAAI]] 1991
* [[Byoung-Tak Zhang]], [[Gerd Veenker]] ('''1991'''). ''[http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=170480&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D170480 Neural networks that teach themselves through genetic discovery of novel examples]''. [http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000500 IEEE IJCNN'91], [https://bi.snu.ac.kr/Publications/Conferences/International Joint Conference on Neural Networks/IJCNN91.pdf pdf]* [[Byoung-Tak Zhang]], [[Gerd Veenker]] ('''1991'''). ''Focused incremental learning for improved generalization with reduced training sets''. ICANN'91, [https://bi.snu.ac.kr/Publications/Conferences/International/ICANN'91.pdf pdf]* [[Stephen Muggleton]] ('''1991'''). ''[https://link.springer.com/article/10.1007/BF03037089 Inductive Logic Programming]''. [https://link.springer.com/journal/354/8/4/page/1 New Generation Computing], Vol. 8, No. 4, [http://www.doc.ic.ac.uk/%7Eshm/Papers/ilp.pdf pdf]
'''1992'''
* [[Miroslav Kubat]] ('''1992'''). ''Introduction to Machine Learning''. [http://dblp.uni-trier.de/db/conf/ac/ai1992.html#Kubat92 Advanced Topics in Artificial Intelligence 1992]
* [[Sebastian Thrun]], [[Tom Mitchell]] ('''1993'''). ''Integrating Inductive Neural Network Learning and Explanation-Based Learning''. [[Conferences#IJCAI1993|IJCAI 1993]], [http://robots.stanford.edu/papers/thrun.EBNN_ijcai93.ps.gz zipped ps]
* [[Alois Heinz]], [[Christoph Hense]] ('''1993'''). ''[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.872 Bootstrap learning of α-β-evaluation functions]''. [http://dblp.uni-trier.de/db/conf/icci/icci1993.html#HeinzH93 ICCI 1993], [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.56.872&rep=rep1&type=pdf pdf]
* [[Nicol N. Schraudolph]], [[Peter Dayan]], [[Terrence J. Sejnowski]] ('''1993'''). ''[https://papers.nips.cc/paper/820-temporal-difference-learning-of-position-evaluation-in-the-game-of-go Temporal Difference Learning of Position Evaluation in the Game of Go]''. [https://papers.nips.cc/book/advances-in-neural-information-processing-systems-6-1993 NIPS 1993]
'''1994'''
* [[Eduardo F. Morales]] ('''1994'''). ''Learning Patterns for Playing Strategies''. [[ICGA Journal#17_1|ICCA Journal, Vol. 17, No. 1]]
* [[Michael Bain]] ('''1994'''). ''Learning Logical Exceptions in Chess''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_Strathclyde University of Strathclyde], [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.729 CitySeerX]
* [[Michael Bain]], [[Stephen Muggleton]] ('''1994'''). ''Learning Optimal Chess Strategies''. Machine Intelligence 13 (eds. K. Furukawa and [[Donald Michie]]), pp. 291-309. Oxford University Press, Oxford, UK. ISBN 0198538502.
* [[Ryszard Michalski]], [[George Tecuci]] ('''1994'''). ''Machine Learning: A Multistrategy Approach, Volume IV''. Morgan Kaufmann, ISBN 1-55860-251-8. [httphttps://booksen.googlewikipedia.comorg/wiki/books?id=sQJ1PMEOOY0C&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google booksMorgan_Kaufmann_Publishers Morgan Kaufmann]
* [[Gerald Tesauro]] ('''1994'''). ''TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play''. [http://www.informatik.uni-trier.de/~ley/db/journals/neco/neco6.html#Tesauro94 Neural Computation Vol. 6, No. 2]
* [[Alberto Maria Segre]], [[Charles Elkan]] ('''1994'''). ''A High-Performance Explanation-Based Learning Algorithm''. [https://en.wikipedia.org/wiki/Artificial_Intelligence_%28journal%29 Artificial Intelligence], Vol. 68, Nos. 1-2
* [[David E. Moriarty]], [[Risto Miikkulainen]] ('''1994'''). ''Evolving Neural Networks to focus Minimax Search''. [[AAAI|AAAI-94]], [http://www.cs.utexas.edu/~ai-lab/pubs/moriarty.focus.pdf pdf]
==1995 ...==
* [[Gerhard Mehlsam]], [[Hermann Kaindl]], [[Wilhelm Barth]] ('''1995'''). ''Feature Construction during Tree Learning''. [http://137.226.34.227/dblp/db/conf/gosler/gosler1995.html GOSLER Final Report] 1995: 391-403
* [[Gerald Tesauro]] ('''1995'''). ''Temporal Difference Learning and TD-Gammon''. [[ACM#Communications|Communications of the ACM]] Vol. 38, No. 3
* [[Sebastian Thrun]] ('''1995'''). ''[http://robots.stanford.edu/papers/thrun.nips7.neuro-chess.html Learning to Play the Game of Chess]''. in [[Gerald Tesauro]], [https://en.wikipedia.org/wiki/David_S._Touretzky David S. Touretzky], [http://mitpress.mit.edu/authors/todd-k-leen Todd K. Leen] (eds.) Advances in Neural Information Processing Systems 7, [https://en.wikipedia.org/wiki/MIT_Press MIT Press]
* [[Marco Wiering]] ('''1995'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&cstart=20&citation_for_view=xVas0I8AAAAJ:roLk4NBRz8UC TD Learning of Game Evaluation Functions with Hierarchical Neural Architectures]''. Master's thesis, [https://en.wikipedia.org/wiki/University_of_Amsterdam University of Amsterdam], [http://webber.physik.uni-freiburg.de/~hon/vorlss02/Literatur/reinforcement/GameEvaluationWithNeuronal.pdf pdf]
* [[Mathematician#MAArbib|Michael A. Arbib]] (ed.) ('''1995, 2002'''). ''[http://mitpress.mit.edu/books/handbook-brain-theory-and-neural-networks The Handbook of Brain Theory and Neural Networks]''. [https://en.wikipedia.org/wiki/MIT_Press The MIT Press]
* [[Nicol N. Schraudolph]] ('''1995'''). ''[http://nic.schraudolph.org/bib2html/b2hd-Schraudolph95 Optimization of Entropy with Neural Networks]''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_California,_San_Diego University of California, San Diego]
* [[Tristan Cazenave]] ('''1996'''). ''Self fuzzy learning''. [http://www.lamsade.dauphine.fr/~cazenave/papers/fuzzy.pdf pdf]
* [[Yoav Freund]], [[Robert Schapire]] ('''1996'''). ''Game Theory, On-line Prediction and Boosting''. [http://dblp.uni-trier.de/db/conf/colt/colt1996.html#FreundS96 COLT 1996], [http://www.cs.princeton.edu/~schapire/papers/FreundSc96b.pdf pdf]
* [[Christopher D. Rosin]], [https://scholar.google.com/citations?user=vqrY_hgAAAAJ&hl=en Richard K. Belew] ('''1996'''). ''A Competitive Approach in Game Learning''. [https://dblp.uni-trier.de/db/conf/colt/colt1996.html COLT 1996], [http://www.sci.brooklyn.cuny.edu/~sklar/teaching/f05/alife/papers/rosin-96competitive.pdf pdf]
'''1997'''
* [[Yoav Freund]], [[Robert Schapire]] ('''1997'''). ''A decision-theoretic generalization of on-line learning and an application to boosting''. [https://en.wikipedia.org/wiki/Journal_of_Computer_and_System_Sciences Journal of Computer and System Sciences], Vol. 55, No. 1, [http://cseweb.ucsd.edu/~yfreund/papers/adaboost.pdf 1996 pdf] » [https://en.wikipedia.org/wiki/AdaBoost AdaBoost]
* [[William Uther]], [[Manuela Veloso|Manuela M. Veloso]] ('''1997'''). ''Adversarial Reinforcement Learning''. [[Carnegie Mellon University]], [http://www.cse.unsw.edu.au/~willu/w/papers/Uther97a.ps ps]
* [[William Uther]], [[Manuela Veloso|Manuela M. Veloso]] ('''1997'''). ''Generalizing Adversarial Reinforcement Learning''. [[Carnegie Mellon University]], [http://www.cse.unsw.edu.au/~willu/w/papers/Uther97b.ps ps]
* [[Marco Wiering]], [[Jürgen Schmidhuber]] ('''1997'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&citation_for_view=xVas0I8AAAAJ:u5HHmVD_uO8C HQ-learning]''. [https://en.wikipedia.org/wiki/Adaptive_Behavior_%28journal%29 Adaptive Behavior], Vol. 6, No 2
'''1998'''
* [[Jonathan Baxter]], [[Andrew Tridgell]], [[Lex Weaver]] ('''1998'''). ''Knightcap: A chess program that learns by combining td(λ) with game-tree search'', Proceedings of the 15th International Conference on Machine Learning, [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.54.8263&rep=rep1&type=pdf pdf] via [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.8263 citeseerX]
* [[Csaba Szepesvári]] ('''1998'''). ''Reinforcement Learning: Theory and Practice''. Proceedings of the 2nd Slovak Conference on Artificial Neural Networks, [http://www.sztaki.hu/%7Eszcsaba/papers/scann98.ps.gz zipped ps]
* [[Richard Sutton]], [[Andrew Barto]] ('''1998'''). ''[https://mitpress.mit.edu/books/reinforcement-learning Reinforcement Learning: An Introduction]''. [https://en.wikipedia.org/wiki/MIT_Press MIT Press]
* [[Ryszard Michalski]], [[Ivan Bratko]], [[Miroslav Kubat]] (eds.) ('''1998'''). ''[httphttps://euwww.wiley.com/WileyCDAen-gb/WileyTitle/productCdMachine+Learning+and+Data+Mining%3A+Methods+and+Applications-p-0471971995.html 9780471971993 Machine Learning and Data Mining: Methods and Applications]''. [https://en.wikipedia.org/wiki/John_Wiley_%26_Sons John Wiley & Sons]
: [[Miroslav Kubat]], [[Ivan Bratko]], [[Ryszard Michalski]] ('''1998'''). ''A Review of Machine Learning Methods''. [http://lacam.di.uniba.it/people/courses/IA/IA1213/IA/letture/MLReview.pdf pdf]
* [[Nobusuke Sasaki]], [[Yasuji Sawada]], [[Jin Yoshimura]] ('''1998'''). ''[http://www.mendeley.com/research/a-neural-network-program-of-tsumego/ A Neural Network Program of Tsume-Go]''. [[CG 1998]] <ref>[https://en.wikipedia.org/wiki/Tsumego Tsumego from Wikipedia]</ref>
* [[Tristan Cazenave]] ('''1998'''). ''Integration of Different Reasoning Modes in a Go Playing and Learning System''. [http://www.lamsade.dauphine.fr/~cazenave/papers/multimodal98.pdf pdf]
* [[Tristan Cazenave]] ('''1998'''). ''Learning with Fuzzy Definitions of Goals''. [http://www.lamsade.dauphine.fr/~cazenave/papers/lpsc.pdf pdf]
* [[Ryszard Michalski]] ('''1998'''). ''Learnable Evolution: Combining Symbolic and Evolutionary Learning''. Proceedings of the Fourth International Workshop on Multistrategy Learning (MSL'98)
* [[Krzysztof Krawiec]], [http://www.informatik.uni-trier.de/~ley/pers/hd/s/Slowinski:Roman.html Roman Slowinski], [http://www.informatik.uni-trier.de/~ley/pers/hd/s/Szczesniak:Irmina.html Irmina Szczesniak] ('''1998'''). ''[http://link.springer.com/chapter/10.1007%2F3-540-69115-4_60 Pedagogical Method for Extraction of Symbolic Knowledge from Neural Networks]''. [http://link.springer.com/book/10.1007%2F3-540-69115-4 Rough Sets and Current Trends in Computing 1998]
* [[Marco Wiering]], [[Jürgen Schmidhuber]] ('''1998'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&citation_for_view=xVas0I8AAAAJ:2osOgNQ5qMEC Fast online Q (λ)]''. [https://en.wikipedia.org/wiki/Machine_Learning_%28journal%29 Machine Learning], Vol. 33, No. 1
'''1999'''
* [[Robert Hyatt]] ('''1999'''). ''[http://www.craftychess.com/hyatt/learning.html Book Learning - a Methodology to Tune an Opening Book Automatically]''. [[ICGA Journal#22_1|ICCA Journal, Vol. 22, No. 1]]
* [http://www.ilsp.gr/homepages/papavasiliou_eng.html Vassilis Papavassiliou], [[Stuart Russell]] ('''1999'''). ''Convergence of reinforcement learning with general function approximators.'' In Proc. IJCAI-99, Stockholm, [http://www.cs.berkeley.edu/~russell/papers/ijcai99-bridge.ps ps]
* [[Philip G. K. Reiser]], [[Patricia J. Riddle]] ('''1999'''). ''[http://link.springer.com/chapter/10.1007%2F3-540-48873-1_19 Evolving Logic Programs to Classify Chess-Endgame Positions]''. [http://link.springer.com/book/10.1007%2F3-540-48873-1 Simulated Evolution and Learning], [https://en.wikipedia.org/wiki/Canberra Canberra], Australia. [http://www.springer.com/series/1244 Lecture Notes in Artificial Intelligence], No. 1585, [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer], [http://stancomb.co.uk/Papers/seal98.pdf pdf] » [[Endgame]]
* [[Marco Wiering]] ('''1999'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&pagesize=100&citation_for_view=xVas0I8AAAAJ:9yKSN-GCB0IC Explorations in Efficient Reinforcement Learning]''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_Amsterdam University of Amsterdam], advisors [[Mathematician#FGroen|Frans Groen]] and [[Jürgen Schmidhuber]]
* [[Mathematician#GEHinton|Geoffrey E. Hinton]], [[Terrence J. Sejnowski]] (eds.) ('''1999'''). ''[https://mitpress.mit.edu/books/unsupervised-learning Unsupervised Learning: Foundations of Neural Computation]''. [https://en.wikipedia.org/wiki/MIT_Press MIT Press]
==2000 ...==
* [[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]
'''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]''. in [[Norio Baba]], [[Lakhmi C. Jain]] (eds.) ('''2001'''). ''[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#19941993|1994 1993 paper]]
* [[Jonathan Schaeffer]], [[Markian Hlynka]], [[Vili Jussila]] ('''2001'''). ''Temporal Difference Learning Applied to a High-Performance Game-Playing Program''. [http://www.informatik.uni-trier.de/~ley/db/conf/ijcai/ijcai2001.html#SchaefferHJ01 IJCAI 2001]
* [[Michael Bowling]], [[Manuela Veloso|Manuela M. Veloso]] ('''2001'''). ''Rational and Convergent Learning in Stochastic Games''. [http://www.informatik.uni-trier.de/~ley/db/conf/ijcai/ijcai2001.html#BowlingV01 IJCAI 2001]
* [[Peter Auer]], [[Nicolò Cesa-Bianchi]], [[Paul Fischer]] ('''2002'''). ''[http://link.springer.com/article/10.1023%2FA%3A1013689704352 Finite-time Analysis of the Multiarmed Bandit Problem]''. [https://en.wikipedia.org/wiki/Machine_Learning_%28journal%29 Machine Learning], Vol. 47, No. 2, [http://homes.di.unimi.it/~cesabian/Pubblicazioni/ml-02.pdf pdf]
* [[Paul E. Utgoff]], [[David J. Stracuzzi]] ('''2002'''). ''Many-Layered Learning''. [https://en.wikipedia.org/wiki/Neural_Computation_%28journal%29 Neural Computation], Vol. 14, No. 10, [http://people.cs.umass.edu/~utgoff/papers/neco-stl.pdf pdf]
* [[Ryan Rifkin]] ('''2002'''). ''Everything Old Is New Again: A Fresh Look at Historical Approaches to Machine Learning''. Ph.D thesis, [[Massachusetts Institute of Technology|MIT]], [http://cbcl.mit.edu/publications/theses/thesis-rifkin.pdf pdf]
'''2003'''
* [[Levente Kocsis]], [[Jaap van den Herik]], [[Jos Uiterwijk]] ('''2003'''). ''Two Learning Algorithms for Forward Pruning''. [[ICGA Journal#26_3|ICGA Journal, Vol 26, No. 3]], [http://zaphod.aml.sztaki.hu/papers/kocsis-ICGA03.ps ps]
* [[Adam Marczyk]] ('''2004'''). ''[http://www.talkorigins.org/faqs/genalg/genalg.html Genetic Algorithms and Evolutionary Computation]'' from the [https://en.wikipedia.org/wiki/TalkOrigins_Archive TalkOrigins Archive]
* [[Petr Aksenov]] ('''2004'''). ''[http://joypub.joensuu.fi/publications/masters_thesis/aksenov_genetic/index_en.html Genetic algorithms for optimising chess position scoring]'', Masters thesis, [ftp://cs.joensuu.fi/pub/Theses/2004_MSc_Aksenov_Petr.pdf pdf]
* [[Marek Strejczek]] ('''2004'''). ''Some aspects of chess programming'', M.Sc. thesis, [[Technical University of Łódź]] , Faculty of Electrical and Electronic Engineering, Department of Computer Science, [http://nesik.republika.pl/download//SomeAspectsOfChessProgramming.zip zipped pdf]
* [http://imranontech.com/ Imran Ghory] ('''2004'''). ''Reinforcement learning in board games''. CSTR-04-004, [http://www.cs.bris.ac.uk/ Department of Computer Science], [https://en.wikipedia.org/wiki/University_of_Bristol University of Bristol]. [http://www.cs.bris.ac.uk/Publications/Papers/2000100.pdf pdf] <ref>[http://www.cs.bris.ac.uk/Publications/pub_master.jsp?type=117 University of Bristol - Department of Computer Science - Technical Reports]</ref>
* [[Mathieu Autonès]], [[Aryel Beck]], [[Phillippe Camacho]], [[Nicolas Lassabe]], [[Hervé Luga]], [[François Scharffe]] ('''2004'''). ''[http://link.springer.com/chapter/10.1007/978-3-540-24650-3_1 Evaluation of Chess Position by Modular Neural network Generated by Genetic Algorithm]''. [http://www.informatik.uni-trier.de/~ley/db/conf/eurogp/eurogp2004.html#AutonesBCLLS04 EuroGP 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'''). ''[http://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&cstart=20&pagesize=80&citation_for_view=xVas0I8AAAAJ:7PzlFSSx8tAC 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
==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]
* [[Yasuhiro Osaki]], [[Kazutomo Shibahara]], [[Yasuhiro Tajima]], [[Yoshiyuki Kotani]] ('''2007'''). ''Reinforcement Learning of Evaluation Functions Using Temporal Difference-Monte Carlo learning method''. [[Conferences#GPW|12th Game Programming Workshop]]
* [[Igor Kononenko]], [http://www.informatik.uni-trier.de/%7Eley/db/indices/a-tree/k/Kukar:Matjaz.html Matjaž Kukar] ('''2007'''). ''[http://mldmbook.fri.uni-lj.si/ Machine Learning and Data Mining: Introduction to Principles and Algorithms]''.
* [[Martin Možina]], [https://dblp.uni-trier.de/pers/hd/z/Zabkar:Jure Jure Žabkar], [[Ivan Bratko]] ('''2007'''). ''Argument Based Machine Learning''. [https://en.wikipedia.org/wiki/Artificial_Intelligence_(journal) Artificial Intelligence], Vol. 171, Nos. 10-15, [https://ailab.si/martin/abml/ABCN2aij_final.pdf pdf preprint]
* [[Krzysztof Krawiec]] ('''2007'''). ''[http://www.sciencedirect.com/science/article/pii/S0167865507002462 Generative Learning of Visual Concepts using Multiobjective Genetic Programming]''. [https://en.wikipedia.org/wiki/Pattern_Recognition_Letters Pattern Recognition Letters], Vol. 28, No. 16
* [[Simon Lucas]] ('''2007'''). ''[http://scholar.google.com/citations?view_op=view_citation&hl=de&user=Jz8DDVAAAAAJ&cstart=20&citation_for_view=Jz8DDVAAAAAJ:QIV2ME_5wuYC Learning to play Othello with N-tuple systems]''. [https://www.chatbots.org/journal/australian_journal_of_intelligent_information_processing_systems/ Australian Journal of Intelligent Information Processing Systems], Special Issue on Game Technology, Vol. 9, No. 4 » [[Othello]]
* [[Byoung-Tak Zhang]] ('''2008'''). ''Hypernetworks: A molecular evolutionary architecture for cognitive learning and memory''. [[IEEE|IEEE Computational Intelligence Magazine]], Vol. 3, No. 3, [https://bi.snu.ac.kr/Publications/Journals/International/IEEE_Comp_Int_3_Zhang.pdf pdf]
* [[Maria Cutumisu]], [[Michael Bowling]], [[Duane Szafron]], [[Richard Sutton]] ('''2008'''). ''Agent Learning using Action-Dependent Learning Rates in Computer Role-Playing Games''. [https://www.aaai.org/Library/AIIDE/aiide08contents.php Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference], [https://webdocs.cs.ualberta.ca/~duane/publications/pdf/2008aiide.pdf pdf]
* [[Balázs Csanád Csáji]], [https://dblp.dagstuhl.de/pers/hd/m/Monostori:L=aacute=szl=oacute= László Monostori] ('''2008, 2014'''). ''Adaptive stochastic resource control: a machine learning approach''. [https://en.wikipedia.org/wiki/Journal_of_Artificial_Intelligence_Research Journal of Artificial Intelligence Research], Vol. 32, [https://arxiv.org/abs/1401.3434 arXiv:1401.3434]
'''2009'''
* [[Hamid Reza Maei]], [[Csaba Szepesvári]], [[Shalabh Bhatnagar]], [[Doina Precup]], [[David Silver]], [[Richard Sutton]] ('''2009'''). ''Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation.'' Accepted in Advances in Neural Information Processing Systems 22, Vancouver, BC. December 2009. MIT Press. [http://books.nips.cc/papers/files/nips22/NIPS2009_1121.pdf pdf]
* [[Martin Možina]] ('''2009'''). ''Argument Based Machine Learning'', PhD Thesis, [http://www.ailab.si/martin/mozina_phd.pdf pdf]
* [[David Silver]] ('''2009'''). ''Reinforcement Learning and Simulation-Based Search''. Ph.D. thesis, [[University of Alberta]]. [http://webdocs.cs.ualberta.ca/~silver/David_Silver/Publications_files/thesis.pdf pdf]
* [[Eli David|Omid David]], [[Jaap van den Herik]], [[Moshe Koppel]], [[Nathan S. Netanyahu]] ('''2009'''). ''Simulating Human Grandmasters: Evolution and Coevolution of Evaluation Functions''. [[ACM]] Genetic and Evolutionary Computation Conference ([http://www.sigevo.org/gecco-2009/ GECCO '09]), pp. 1483 - 1489, [https://en.wikipediaarxiv.org/wikiabs/Montreal Montreal], Canada, [http1711.06840 arXiv://www1711.omiddavid.com/pubs/gm-simul.pdf pdf06840]* [[Eli David|Omid David]] ('''2009'''). ''Genetic Algorithms Based Learning for Evolving Intelligent Organisms''. Ph.D. Thesis <ref>[[Dap Hartmann]] ('''2010'''). ''Mimicking the Black Box - Genetically evolving evaluation functions and search algorithms''. Review on Omid David's Ph.D. Thesis, [[ICGA Journal#33_1|ICGA Journal, Vol 33, No. 1]]</ref>
* [[Nur Merve Amil]], [[Nicolas Bredèche]], [[Christian Gagné]], [[Sylvain Gelly]], [[Marc Schoenauer]], [[Olivier Teytaud]] ('''2009'''). ''A Statistical Learning Perspective of Genetic Programming''. EuroGP 2009, [http://hal.inria.fr/docs/00/36/97/82/PDF/eurogp.pdf pdf]
* [[Richard Sutton]], [[Hamid Reza Maei]], [[Doina Precup]], [[Shalabh Bhatnagar]], [[David Silver]], [[Csaba Szepesvári]], [[Eric Wiewiora]]. ('''2009'''). ''Fast Gradient-Descent Methods for Temporal-Difference Learning with Linear Function Approximation''. In Proceedings of the 26th International Conference on Machine Learning (ICML-09). [http://www.sztaki.hu/~szcsaba/papers/GTD-ICML09.pdf pdf]
* [[Mark Levene]], [[Trevor Fenner]] ('''2009'''). ''A Methodology for Learning Players' Styles from Game Records''. [http://arxiv.org/abs/0904.2595v1 arXiv:0904.2595v1]
* [[Mathematician#THastie|Trevor Hastie]], [[Mathematician#RTibshirani|Robert Tibshirani]], [https://en.wikipedia.org/wiki/Jerome_H._Friedman Jerome Friedman] ('''2009'''). ''[http://www.springer.com/book/9780387848570 The Elements of Statistical Learning: Data Mining, Inference, and Prediction]''. Second Edition, [https://de.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
* [https://dblp.uni-trier.de/pers/hd/h/Hall:Mark_A= Mark A. Hall], [https://dblp.uni-trier.de/pers/hd/f/Frank:Eibe Eibe Frank], [[Geoffrey Holmes]], [[Bernhard Pfahringer]], [https://dblp.uni-trier.de/pers/hd/r/Reutemann:Peter Peter Reutemann], [[Ian H. Witten]] ('''2009'''). ''The WEKA data mining software: an update''. [https://dblp.uni-trier.de/db/journals/sigkdd/sigkdd11.html SIGKDD Explorations], Vol. 11, No. 1, [https://www.kdd.org/exploration_files/p2V11n1.pdf pdf] <ref>[https://en.wikipedia.org/wiki/Weka_(machine_learning) Weka (machine learning) from Wikipedia]</ref>
==2010 ...==
* [[Johannes Fürnkranz]], [https://de.wikipedia.org/wiki/Eyke_H%C3%BCllermeier Eyke Hüllermeier] (eds.) ('''2010'''). ''[https://link.springer.com/book/10.1007/978-3-642-14125-6 Preference Learning]''. [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
* [https://dblp.uni-trier.de/pers/hd/f/Frank:Eibe Eibe Frank], [https://dblp.uni-trier.de/pers/hd/h/Hall:Mark_A= Mark A. Hall], [[Geoffrey Holmes]], [https://dblp.uni-trier.de/pers/hd/k/Kirkby:Richard Richard Kirkby], [[Bernhard Pfahringer]], [[Ian H. Witten]], [https://dblp.uni-trier.de/pers/hd/t/Trigg:Leonard_E= Len Trigg] ('''2010'''). ''[https://link.springer.com/chapter/10.1007/978-0-387-09823-4_66 Weka-A Machine Learning Workbench for Data Mining]''. [https://link.springer.com/book/10.1007/978-0-387-09823-4 Data Mining and Knowledge Discovery Handbook], [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
* [[Jacek Mańdziuk]] ('''2010'''). ''[http://link.springer.com/book/10.1007%2F978-3-642-11678-0 Knowledge-Free and Learning-Based Methods in Intelligent Game Playing]''. [http://link.springer.com/bookseries/7092 Studies in Computational Intelligence], Vol. 276, [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
* [[Joel Veness]], [[Kee Siong Ng]], [[Marcus Hutter]], [[David Silver]] ('''2010'''). ''Reinforcement Learning via AIXI Approximation''. Association for the Advancement of Artificial Intelligence (AAAI), [http://jveness.info/publications/veness_rl_via_aixi_approx.pdf pdf]
* [[Omid Eli David]], [[Moshe Koppel]], [[Nathan S. Netanyahu]] ('''2010'''). ''[http://www.springerlink.com/content/3346t8432n718821 Expert-Driven Genetic Algorithms for Simulating Evaluation Functions]''. [http://www.omiddavid.com/pubs/expert-driven.pdf pdf]* [[|Omid David]], [[Nathan S. Netanyahu]], Yoav Rosenberg, Moshe Shimoni ('''2010'''). ''Genetic Algorithms for Automatic Classification of Moving Objects''. [[ACM]] Genetic and Evolutionary Computation Conference ([http://www.sigevo.org/gecco-2010/ GECCO '10]), [https://en.wikipedia.org/wiki/Portland,_Oregon Portland, OR], [http://www.omiddavid.com/pubs/object-classification.pdf pdf]* [[Eli David|Omid David]], [[Moshe Koppel]], [[Nathan S. Netanyahu]] ('''2010'''). ''Genetic Algorithms for Automatic Search Tuning''. [[ICGA Journal#33_2|ICGA Journal, Vol . 33, No. 2]]
* [[Mesut Kirci]] ('''2010'''). ''Feature Learning using State Differences''. Master's thesis, Department of Computing Science, [[University of Alberta]], [http://repository.library.ualberta.ca/dspace/bitstream/10048/1011/1/kirci_mesut_spring+2010.pdf pdf] » [[General Game Playing]]
* [[Amine Bourki]], [[Matthieu Coulm]], [[Philippe Rolet]], [[Olivier Teytaud]], [[Paul Vayssière]] ('''2010'''). ''[http://hal.inria.fr/inria-00467796/en/ Parameter Tuning by Simple Regret Algorithms and Multiple Simultaneous Hypothesis Testing]''. [http://hal.inria.fr/docs/00/46/77/96/PDF/tosubmit.pdf pdf]
* [[Edward P. Manning]] ('''2010'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5409565 Using Resource-Limited Nash Memory to Improve an Othello Evaluation Function]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 2, No. 1 » [[Othello]]
* [[Edward P. Manning]] ('''2010'''). ''[http://dl.acm.org/citation.cfm?id=1830667 Coevolution in a Large Search Space using Resource-limited Nash Memory]''. [http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2010.html#Manning10 GECCO '10] » [[Othello]]
* [[Marco Wiering]] ('''2010'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&cstart=20&citation_for_view=xVas0I8AAAAJ:_kc_bZDykSQC Self-play and using an expert to learn to play backgammon with temporal difference learning]''. [http://www.scirp.org/journal/jilsa/ Journal of Intelligent Learning Systems and Applications], Vol. 2, No. 2
'''2011'''
* [[Joel Veness]] ('''2011'''). ''Approximate Universal Artificial Intelligence and Self-Play Learning for Games''. Ph.D. thesis, [https://en.wikipedia.org/wiki/University_of_New_South_Wales University of New South Wales], supervisors: [[Kee Siong Ng]], [[Marcus Hutter]], [[Alan Blair]], [[William Uther]], [[John Lloyd]]; [http://jveness.info/publications/veness_phd_thesis_final.pdf pdf]
* [[Marcin Szubert]], [[Wojciech Jaśkowski]], [[Krzysztof Krawiec]] ('''2011'''). ''Learning Board Evaluation Function for Othello by Hybridizing Coevolution with Temporal Difference Learning''. [http://control.ibspan.waw.pl:3000/mainpage Control and Cybernetics], Vol. 40, No. 3, [http://www.cs.put.poznan.pl/wjaskowski/pub/papers/szubert2011learning.pdf pdf] » [[Othello]]
* [[Hamid Reza Maei]] ('''2011'''). ''Gradient Temporal-Difference Learning Algorithms''. Ph.D. thesis, [[University of Alberta]], advisor [[Richard Sutton]], [http://webdocs.cs.ualberta.ca/~sutton/papers/maei-thesis-2011.pdf pdf]
* [[Eli David|Omid David]], [[Moshe Koppel]], [[Nathan S. Netanyahu]] ('''2011'''). ''[https://link.springer.com/article/10.1007/s10710-010-9103-4 Expert-Driven Genetic Algorithms for Simulating Evaluation Functions]''. [https://www.springer.com/journal/10710 Genetic Programming and Evolvable Machines], Vol. 12, No. 1, [https://arxiv.org/abs/1711.06841 arXiv:1711.06841]
'''2012'''
* [[Marco Wiering]], [http://martijnvanotterlo.nl/ Martijn Van Otterlo] ('''2012'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&citation_for_view=xVas0I8AAAAJ:abG-DnoFyZgC Reinforcement learning: State-of-the-art]''. [http://link.springer.com/book/10.1007/978-3-642-27645-3 Adaptation, Learning, and Optimization, Vol. 12], [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
: [[István Szita]] ('''2012'''). ''[http://link.springer.com/chapter/10.1007%2F978-3-642-27645-3_17 Reinforcement Learning in Games]''. Chapter 17
* [http://dblp.uni-trier.de/pers/hd/d/Dries:Sjoerd_van_den Sjoerd van den Dries], [[Marco Wiering]] ('''2012'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&cstart=40&citation_for_view=xVas0I8AAAAJ:P5F9QuxV20EC Neural-fitted TD-leaf learning for playing Othello with structured neural networks]''. [[IEEE#NN|IEEE Transactions on Neural Networks and Learning Systems]], Vol. 23, No. 11
* [[Marcin Szubert]], [[Wojciech Jaśkowski]], [[Paweł Liskowski]], [[Krzysztof Krawiec]] ('''2013'''). ''Shaping Fitness Function for Evolutionary Learning of Game Strategies''. [http://www.informatik.uni-trier.de/~ley/db/conf/gecco/gecco2013.html#SzubertJLK13 GECCO 2013], [http://www.cs.put.poznan.pl/wjaskowski/pub/papers/szubert2013shaping.pdf pdf]
* [[Marcin Szubert]], [[Wojciech Jaśkowski]], [[Krzysztof Krawiec]] ('''2013'''). ''[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6504736 On Scalability, Generalization, and Hybridization of Coevolutionary Learning: a Case Study for Othello]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 5, No. 3 » [[Othello]]
* [http://dblp.uni-trier.de/pers/hd/r/Ree:M=_van_der Michiel van der Ree], [[Marco Wiering]] ('''2013'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&cstart=60&pagesize=80&citation_for_view=xVas0I8AAAAJ:K3LRdlH-MEoC Reinforcement Learning in the Game of Othello: Learning Against a Fixed Opponent and Learning from Self-Play]''. [http://dblp.uni-trier.de/db/conf/adprl/adprl2013.html#ReeW13 ADPRL 2013]* [http://dblp.uni-trier.de/pers/hd/b/Bom:Luuk Luuk Bom], [http://dblp.uni-trier.de/pers/hd/h/Henken:Ruud Ruud Henken], [[Marco Wiering]] ('''2013'''). ''[https://scholar.google.com/citations?view_op=view_citation&hl=en&user=xVas0I8AAAAJ&cstart=40&citation_for_view=xVas0I8AAAAJ:l7t_Zn2s7bgC Reinforcement Learning to Train Ms. Pac-Man Using Higher-order Action-relative Inputs]''. [http://dblp.uni-trier.de/db/conf/adprl/adprl2013.html#BomHW13 ADPRL 2013] <ref>[https://en.wikipedia.org/wiki/Ms._Pac-Man Ms. Pac-Man from Wikipedia]</ref>
* [[Peter Auer]], [[Marcus Hutter]], [[Laurent Orseau]] ('''2013'''). ''[http://drops.dagstuhl.de/opus/volltexte/2013/4340/ Reinforcement Learning]''. [http://dblp.uni-trier.de/db/journals/dagstuhl-reports/dagstuhl-reports3.html#AuerHO13 Dagstuhl Reports, Vol. 3, No. 8], DOI: [http://drops.dagstuhl.de/opus/volltexte/2013/4340/ 10.4230/DagRep.3.8.1], URN: [http://drops.dagstuhl.de/opus/volltexte/2013/4340/ urn:nbn:de:0030-drops-43409]
* [[Igor Roizen]], [[Judea Pearl]] ('''2013'''). ''Learning Link-Probabilities in Causal Trees.'' [https://arxiv.org/abs/1304.3103 arXiv:1304.3103]
* [[Volodymyr Mnih]], [[Koray Kavukcuoglu]], [[David Silver]], [[Alex Graves]], [[Ioannis Antonoglou]], [[Daan Wierstra]], [[Martin Riedmiller]] ('''2013'''). ''Playing Atari with Deep Reinforcement Learning''. [http://arxiv.org/abs/1312.5602 arXiv:1312.5602] <ref>[http://www.nervanasys.com/demystifying-deep-reinforcement-learning/ Demystifying Deep Reinforcement Learning] by [http://www.nervanasys.com/author/tambet/ Tambet Matiisen], [http://www.nervanasys.com/ Nervana], December 21, 2015</ref> <ref>[http://www.google.com/patents/US20150100530 Patent US20150100530 - Methods and apparatus for reinforcement learning - Google Patents]</ref>
'''2014'''
* [[Eli David|Omid David]], [[Jaap van den Herik]], [[Moshe Koppel]], [[Nathan S. Netanyahu]] ('''2014'''). ''Genetic Algorithms for Evolving Computer Chess Programs''. [[IEEE#EC|IEEE Transactions on Evolutionary Computation]], [httphttps://www.genetic-programmingarxiv.org/hc2014abs/David-Paper1711.pdf pdf] <ref>[http08337 arXiv://www1711.liacs.nl/nieuws/jaap-van-den-herik-wint-humies-award-2014/ Jaap van den Herik wint Humies Award 2014 - LIACS - Leiden Institute of Advanced Computer Science08337]</ref>
* [[Wojciech Jaśkowski]], [[Marcin Szubert]], [[Paweł Liskowski]] ('''2014'''). ''Multi-Criteria Comparison of Coevolution and Temporal Difference Learning on Othello''. [http://www.evostar.org/2014/ EvoApplications 2014], [http://www.springer.com/computer/theoretical+computer+science/book/978-3-662-45522-7 Springer, volume 8602] » [[Othello]]
* [[Marcin Szubert]], [[Wojciech Jaśkowski]] ('''2014'''). ''Temporal Difference Learning of N-Tuple Networks for the Game 2048''. [[IEEE#CIG|IEEE Conference on Computational Intelligence and Games]], [http://www.cs.put.poznan.pl/mszubert/pub/szubert2014cig.pdf pdf] <ref>[https://en.wikipedia.org/wiki/2048_%28video_game%29 2048 (video game) from Wikipedia]</ref>
* [[Hado van Hasselt]], [[Arthur Guez]], [[David Silver]] ('''2015'''). ''Deep Reinforcement Learning with Double Q-learning''. [http://arxiv.org/abs/1509.06461 arXiv:1509.06461]
* [[Tom Schaul]], [[John Quan]], [[Ioannis Antonoglou]], [[David Silver]] ('''2015'''). ''Prioritized Experience Replay''. [http://arxiv.org/abs/1511.05952 arXiv:1511.05952]
* [[Miroslav Kubat]] ('''2015'''). ''[httphttps://www.springer.com/us/book/9783319348865#otherversion=9783319200095 An Introduction to Machine Learning]''. [https://deen.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
* [[Christian Wirth]], [[Johannes Fürnkranz]] ('''2015'''). ''[http://ieeexplore.ieee.org/document/6861960/ On Learning From Game Annotations]''. [[IEEE#TOCIAIGAMES|IEEE Transactions on Computational Intelligence and AI in Games]], Vol. 7, No. 3
'''2016'''
* [[Ziyu Wang]], [[Nando de Freitas]], [[Marc Lanctot]] ('''2016'''). ''Dueling Network Architectures for Deep Reinforcement Learning''. [http://arxiv.org/abs/1511.06581 arXiv:1511.06581]
* [[Jialin Liu]], [[Olivier Teytaud]], [[Tristan Cazenave]] ('''2016'''). ''Fast seed-learning algorithms for games''. [[CG 2016]]
* [[Omid Eli David|Omid E. David]], [[Nathan S. Netanyahu]], [[Lior Wolf]] ('''2016'''). ''[http://link.springer.com/chapter/10.1007%2F978-3-319-44781-0_11 DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess]''. [http://icann2016.org/ ICAAN 2016], [https://en.wikipedia.org/wiki/Lecture_Notes_in_Computer_Science Lecture Notes in Computer Science], Vol. 9887, [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer], [http://www.cs.tau.ac.il/~wolf/papers/deepchess.pdf pdf preprint] » [[DeepChess]] <ref>[http://www.talkchess.com/forum/viewtopic.php?t=61748 DeepChess: Another deep-learning based chess program] by [[Matthew Lai]], [[CCC]], October 17, 2016</ref> <ref>[http://icann2016.org/index.php/conference-programme/recipients-of-the-best-paper-awards/ ICANN 2016 | Recipients of the best paper awards]</ref>
* [https://www.linkedin.com/in/ian-goodfellow-b7187213 Ian Goodfellow], [https://en.wikipedia.org/wiki/Yoshua_Bengio Yoshua Bengio], [https://www.linkedin.com/in/aaron-courville-53a63459 Aaron Courville] ('''2016'''). ''[http://www.deeplearningbook.org/ Deep Learning]''. [https://en.wikipedia.org/wiki/MIT_Press MIT Press]
* [[Max Jaderberg]], [[Volodymyr Mnih]], [[Wojciech Marian Czarnecki]], [[Tom Schaul]], [[Joel Z. Leibo]], [[David Silver]], [[Koray Kavukcuoglu]] ('''2016'''). ''Reinforcement Learning with Unsupervised Auxiliary Tasks''. [https://arxiv.org/abs/1611.05397v1 arXiv:1611.05397v1]
* [[Ian H. Witten]], [https://dblp.uni-trier.de/pers/hd/f/Frank:Eibe Eibe Frank], [https://dblp.uni-trier.de/pers/hd/h/Hall:Mark_A= Mark A. Hall], [http://www.professeurs.polymtl.ca/christopher.pal/ Christopher Pal] ('''2016'''). ''[https://www.cs.waikato.ac.nz/~ml/weka/book.html Data Mining: Practical Machine Learning Tools and Techniques]''. 4th Edition, [https://en.wikipedia.org/wiki/Morgan_Kaufmann_Publishers Morgan Kaufmann]
'''2017'''
* [[Stephen Muggleton]] ('''2017'''). ''Meta-Interpretive Learning: Achievements and Challenges''. Invited Paper, [https://dblp.uni-trier.de/db/conf/ruleml/ruleml2017.html RuleML+RR 2017], [https://www.doc.ic.ac.uk/~shm/Papers/rulemlabs.pdf pdf]
* [[Muthuraman Chidambaram]], [[Yanjun Qi]] ('''2017'''). ''Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently''. [https://arxiv.org/abs/1702.06762v1 arXiv:1702.06762v1] <ref>[http://www.talkchess.com/forum/viewtopic.php?t=63252 Using GAN to play chess] by Evgeniy Zheltonozhskiy, [[CCC]], February 23, 2017</ref> » [[Neural Networks]]
* [[Johannes Fürnkranz]] ('''2017'''). ''Machine Learning and Game Playing''. 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://en.wikipedia.org/wiki/Boston Boston, MA]
* [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Matthew Lai]], [[Arthur Guez]], [[Marc Lanctot]], [[Laurent Sifre]], [[Dharshan Kumaran]], [[Thore Graepel]], [[Timothy Lillicrap]], [[Karen Simonyan]], [[Demis Hassabis]] ('''2017'''). ''Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm''. [https://arxiv.org/abs/1712.01815 arXiv:1712.01815] » [[AlphaZero]]
* [[Miroslav Kubat]] ('''2017'''). ''[https://www.springer.com/gp/book/9783319639123 An Introduction to Machine Learning]''. Second Edition, [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]
'''2018'''
* [[Arthur Guez]], [[Théophane Weber]], [[Ioannis Antonoglou]], [[Karen Simonyan]], [[Oriol Vinyals]], [[Daan Wierstra]], [[Rémi Munos]], [[David Silver]] ('''2018'''). ''Learning to Search with MCTSnets''. [https://arxiv.org/abs/1802.04697 arXiv:1802.04697] » [[Monte-Carlo Tree Search]]
* [[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]]'''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]* [[Frank Hutter]], [https://dblp.org/pers/hd/k/Kotthoff:Lars Lars Kotthoff], [https://dblp.org/pers/hd/v/Vanschoren:Joaquin Joaquin Vanschoren] (eds.) ('''2019'''). ''[https://link.springer.com/book/10.1007%2F978-3-030-05318-5 Automated Machine Learning]''. [https://en.wikipedia.org/wiki/Springer_Science%2BBusiness_Media Springer]* [[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>
=Forum Posts=
==1998 ...==
* [https://www.stmintz.com/ccc/index.php?id=16136 Opponent specific learning...] by [[Daniel Homan]], [[CCC]], March 26, 1998
* [https://www.stmintz.com/ccc/index.php?id=17861 Book learning and rating bias] by [[Don Dailey]], [[CCC]], May 01, 1998
* [https://www.stmintz.com/ccc/index.php?id=25754 BookLearning Under the Microscope!!!] by Robert Henry Durrett, [[CCC]], August 31, 1998
* [http://www.talkchess.com/forum/viewtopic.php?t=56313 Position learning and opening books] by Forrest Hoch, [[CCC]], May 11, 2015
* [http://www.talkchess.com/forum/viewtopic.php?t=61861 A database for learning evaluation functions] by [[Álvaro Begué]], [[CCC]], October 28, 2016 » [[Automated Tuning]], [[Evaluation]], [[Texel's Tuning Method]]
* [http://www.talkchess.com/forum3/viewtopic.php?f=7&t=72020 A book on machine learning] by Mehdi Amini, [[CCC]], October 06, 2019
=External Links=
* [https://en.wikipedia.org/wiki/List_of_machine_learning_concepts List of machine learning concepts from Wikipedia]
* [https://en.wikipedia.org/wiki/Apprenticeship_learning Apprenticeship learning from Wikipedia]
* [https://en.wikipedia.org/wiki/Automated_machine_learning Automated machine learning from Wikipedia]
* [https://en.wikipedia.org/wiki/Data_mining Data mining from Wikipeadia]
* [https://en.wikipedia.org/wiki/Ensemble_learning Ensemble learning from Wikipedia]
** [https://en.wikipedia.org/wiki/Bootstrap_aggregating Bootstrap aggregating from Wikipedia]
* [https://en.wikipedia.org/wiki/Explanation-based_learning Explanation-based learning from Wikipedia]
* [https://en.wikipedia.org/wiki/Meta_learning_%28computer_science%29 Meta Learning from Wikipedia]
* [http://www.aihorizon.com/essays/generalai/no_free_lunch_machine_learning.htm AI Horizon: Machine Learning, Part III: Testing Algorithms, and The "No Free Lunch Theorem"]
==Chess==
* [http://archive.ics.uci.edu/ml/datasets/Chess+%28King-Rook+vs.+King-Pawn%29 UCI Machine Learning Repository: Chess (King-Rook vs. King-Pawn) Data Set] by [[Alen Shapiro]]
* [https://en.chessbase.com/post/standing-on-the-shoulders-of-giants Standing on the shoulders of giants] by [[Albert Silver]], [[ChessBase|ChessBase News]], September 18, 2019
==Supervised Learning==
* [https://en.wikipedia.org/wiki/Supervised_learning Supervised learning from Wikipedia]
* [http://www.scholarpedia.org/article/Category:Supervised_learning Category: Supervised learning - Scholarpedia]
* [https://en.wikipedia.org/wiki/Boosting_%28machine_learning%29 Boosting (machine learning) from Wikipedia]
* [https://en.wikipedia.org/wiki/Computational_learning_theory Computational learning theory from Wikipedia]
* [https://en.wikipedia.org/wiki/Support_vector_machine Support vector machine from Wikipedia]
* [https://en.wikipedia.org/wiki/Statistical_learning_theory Statistical learning theory from Wikipedia]
* [https://en.wikipedia.org/wiki/Statistical_classification Statistical classification from Wikipedia]
* [https://en.wikipedia.org/wiki/Statistical_mechanics Statistical mechanics from Wikipedia]
* [https://en.wikipedia.org/wiki/Bayesian_network Bayesian network from Wikipedia]
* [https://en.wikipedia.org/wiki/Mean_squared_error Mean squared error from Wikipedia]
* [https://en.wikipedia.org/wiki/Regression_analysis Regression analysis from Wikipedia]
* [https://en.wikipedia.org/wiki/Probability Probability from Wikipedia]
* [https://en.wikipedia.org/wiki/Probability_theory Probability theory from Wikipedia]
* [https://en.wikipedia.org/wiki/Probability_density_function Probability density function from Wikipedia]
* [https://en.wikipedia.org/wiki/Probability_distribution Probability distribution from Wikipedia]
* [https://en.wikipedia.org/wiki/Probability_measure Probability measure from Wikipedia]
* [https://en.wikipedia.org/wiki/Probability_space Probability space from Wikipedia]
* [https://en.wikipedia.org/wiki/Pseudorandomness Pseudorandomness from Wikipedia]
* [https://en.wikipedia.org/wiki/Randomness Randomness from Wikipedia]
* [https://en.wikipedia.org/wiki/Vapnik%E2%80%93Chervonenkis_theory Vapnik–Chervonenkis theory from Wikipedia]
* [https://en.wikipedia.org/wiki/VC_dimension VC dimension from Wikipedia]
* [http://www.scholarpedia.org/article/Hopfield_network Hopfield network - Scholarpedia]
* [https://en.wikipedia.org/wiki/Long_short_term_memory Long short term memory from Wikipedia]
==Courses==
* [http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html Advanced Topics: RL] by [[David Silver]]
=References=
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