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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> .
<span id="Programs"></span>
=Programs=
* [[Allie]]
* [[AlphaZero]]
* [[Alexs]]
* [[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'''). ''[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]''. [https://en.wikipedia.org/wiki/Morgan_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]]
* [[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]]
* [[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
* [[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]
* [[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]
* [[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]
* [[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 ...==
* [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]
* [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]
* [[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]
=Forum Posts=
* [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/Explanation-based_learning Explanation-based learning from Wikipedia]
=References=
<references />
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