Difference between revisions of "Learning"

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* [[Marvin Minsky]] ('''1954'''). ''Neural Nets and the Brain Model Problem''. Ph.D. dissertation, [https://en.wikipedia.org/wiki/Princeton_University Princeton University]
 
* [[Marvin Minsky]] ('''1954'''). ''Neural Nets and the Brain Model Problem''. Ph.D. dissertation, [https://en.wikipedia.org/wiki/Princeton_University Princeton University]
 
==1955 ...==
 
==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  
 
* [[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]
 
: [[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]
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* [[Jacques Pitrat]] ('''1976'''). ''Realization of a Program Learning to Find Combinations at Chess.'' Computer Oriented Learning Processes (ed. J. Simon). Noordhoff, Groningen, The Netherlands.
 
* [[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]
 
* [[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''. [http://www.doc.ic.ac.uk/~shm/MI/mi8.html Machine Intelligence 8], [http://www.mli.gmu.edu/papers/69-78/77-1.pdf pdf]
+
* [[Ryszard Michalski]], [[Pericles Negri]] ('''1977'''). ''An experiment on inductive learning in chess endgames''. [https://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
 
* [[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.  
 
* [[Richard Sutton]] ('''1978'''). ''Single channel theory: A neuronal theory of learning''. Brain Theory Newsletter 3, No. 3/4, pp. 72-75.  
Line 134: Line 135:
 
* [[Alen Shapiro]], [[Tim Niblett]] ('''1982'''). ''Automatic Induction of Classification Rules for Chess End game.'' [[Advances in Computer Chess 3]]
 
* [[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]]
 
* [[Thomas Nitsche]] ('''1982'''). ''A Learning Chess Program.'' [[Advances in Computer Chess 3]]
* [[Ryszard Michalski]], [[Jaime Carbonell]], [[Tom Mitchell]] ('''1983'''). ''Machine Learning: An Artificial Intelligence Approach''. Tioga Publishing Company, ISBN 0-935382-05-4. [http://books.google.com/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 books]
+
* [[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]''. [https://en.wikipedia.org/wiki/Springer_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  
 
* [[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)  
 
* [[Alen Shapiro]] ('''1983'''). ''The Role of Structured Induction in Expert Systems''. [[University of Edinburgh]], Machine Intelligence Research Unit (Ph.D. thesis)  
Line 146: Line 147:
 
* [[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]
 
* [[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.
 
* [[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'''). ''Machine Learning: An Artificial Intelligence Approach''. Morgan Kaufmann, ISBN 0-934613-09-5. [http://books.google.com/books?id=TWzuUd5gsnkC&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google books]
+
* [[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 Uncertainty in Artificial Intelligence
+
* [[Igor Roizen]], [[Judea Pearl]] ('''1985'''). ''Learning Link Probabilities in Causal Trees.'' [[Laveen Kanal#Uncertainty AI 1|Uncertainty in Artificial Intelligence 1]]
 
'''1986'''
 
'''1986'''
 
* [[Steven Skiena]] ('''1986'''). ''An Overview of Machine Learning in Chess.'' [[ICGA Journal#9_1|ICCA Journal, Vol. 9, No. 1]]
 
* [[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].
+
* [[Jens Christensen]], [[Richard Korf]] ('''1986'''). ''A Unified Theory of Heuristic Evaluation functions and Its Applications to Learning.'' Proceedings of the AAAI-86, [http://www.aaai.org/Papers/AAAI/1986/AAAI86-023.pdf pdf].
* [[Ryszard Michalski]], [[Jaime Carbonell]], [[Tom Mitchell]] ('''1986'''). ''Machine Learning: An Artificial Intelligence Approach, Volume II''. Morgan Kaufmann, ISBN 0-934613-00-1. [http://books.google.com/books?id=f9RylgKpHZsC&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google books]
+
* [[Ryszard Michalski]], [[Jaime Carbonell]], [[Tom Mitchell]] ('''1986'''). ''[https://dl.acm.org/citation.cfm?id=21934 Machine Learning: An Artificial Intelligence Approach, Volume II]''. [https://en.wikipedia.org/wiki/Morgan_Kaufmann_Publishers Morgan Kaufmann]
* [[Tom Mitchell]], [[Jaime Carbonell]], [[Ryszard Michalski]] ('''1986'''). ''[http://link.springer.com/book/10.1007/978-1-4613-2279-5 Machine Learning: A Guide to Current Research]''. The Kluwer International Series in Engineering and Computer Science, Vol. 12
+
* [[Tom Mitchell]], [[Jaime Carbonell]], [[Ryszard Michalski]] ('''1986'''). ''[https://link.springer.com/book/10.1007%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
 
* [[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'''
 
'''1987'''
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* [[Bruce Abramson]] ('''1990'''). ''On Learning and Testing Evaluation Functions.'' Journal of Experimental and Theoretical Artificial Intelligence 2: 241-251.
 
* [[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]]
 
* [[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'''). ''Machine Learning: An Artificial Intelligence Approach, Volume III''. Morgan Kaufmann, ISBN 1-55860-119-8. [http://books.google.com/books?id=UDqCeuwVkkcC&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google books]
+
* [[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]''. [https://en.wikipedia.org/wiki/Morgan_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]
 
* [[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'''
 
'''1991'''
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* [[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]
 
* [[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]
 
* [[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'''
 
'''1994'''
 
* [[Eduardo F. Morales]] ('''1994'''). ''Learning Patterns for Playing Strategies''. [[ICGA Journal#17_1|ICCA Journal, Vol. 17, No. 1]]
 
* [[Eduardo F. Morales]] ('''1994'''). ''Learning Patterns for Playing Strategies''. [[ICGA Journal#17_1|ICCA Journal, Vol. 17, No. 1]]
Line 215: Line 217:
 
* [[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]] ('''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.
 
* [[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. [http://books.google.com/books?id=sQJ1PMEOOY0C&dq=isbn%3A0935382054&hl=de&source=gbs_book_other_versions google books]
+
* [[Ryszard Michalski]], [[George Tecuci]] ('''1994'''). ''Machine Learning: A Multistrategy Approach, Volume IV''. [https://en.wikipedia.org/wiki/Morgan_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]
 
* [[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
 
* [[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]
 
* [[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]
* [[Nicol N. Schraudolph]], [[Peter Dayan]], [[Terrence J. Sejnowski]] ('''1994'''). ''[http://nic.schraudolph.org/bib2html/b2hd-SchDaySej94.html Temporal Difference Learning of Position Evaluation in the Game of Go]''. [http://papers.nips.cc/book/advances-in-neural-information-processing-systems-6-1993 Advances in Neural Information Processing Systems 6]
 
 
==1995 ...==  
 
==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
 
* [[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
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* [[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]
 
* [[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]
 
* [[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'''). ''[http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0471971995.html Machine Learning and Data Mining: Methods and Applications]''. [https://en.wikipedia.org/wiki/John_Wiley_%26_Sons John Wiley & Sons]
+
* [[Ryszard Michalski]], [[Ivan Bratko]], [[Miroslav Kubat]] (eds.) ('''1998'''). ''[https://www.wiley.com/en-gb/Machine+Learning+and+Data+Mining%3A+Methods+and+Applications-p-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]
 
: [[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>
 
* [[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>
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* [[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'''). ''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]
 
* [[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)
+
* [[Ryszard Michalski]] ('''1998'''). ''Learnable Evolution: Combining Symbolic and Evolutionary Learning''. Proceedings of the Fourth International Workshop on Multistrategy Learning
 
* [[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]
 
* [[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'''). ''Fast online Q (λ)''. [https://en.wikipedia.org/wiki/Machine_Learning_%28journal%29 Machine Learning], Vol. 33, No. 1
 
* [[Marco Wiering]],  [[Jürgen Schmidhuber]] ('''1998'''). ''Fast online Q (λ)''. [https://en.wikipedia.org/wiki/Machine_Learning_%28journal%29 Machine Learning], Vol. 33, No. 1
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* [[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]
 
* [[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'''
 
'''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#1994|1994 paper]]
+
* [[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]]
 
* [[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]
 
* [[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]
 
* [[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]
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* [[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]
 
* [[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]
 
* [[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'', [[Technical University of Łódź]] , Faculty of Electrical and Electronic Engineering, Department of Computer Science, [http://nesik.republika.pl/download//SomeAspectsOfChessProgramming.zip zipped pdf]
+
* [[Marek Strejczek]] ('''2004'''). ''Some aspects of chess programming'', M.Sc. thesis, [[Technical University of Łódź]]
 
* [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>
 
* [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]
 
* [[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]
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* [[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]
 
* [[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]
 
* [[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'''
 
'''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]
 
* [[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]
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* [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]
 
* [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]
 
* [[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'''
 
'''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]
 
* [[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]
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* [[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]]
 
* [[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]
 
* [[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]]
  
 
=Forum Posts=
 
=Forum Posts=
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* [https://en.wikipedia.org/wiki/List_of_machine_learning_concepts List of machine learning concepts from Wikipedia]
 
* [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/Apprenticeship_learning Apprenticeship 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/Ensemble_learning Ensemble learning from Wikipedia]
 
* [https://en.wikipedia.org/wiki/Explanation-based_learning Explanation-based learning from Wikipedia]
 
* [https://en.wikipedia.org/wiki/Explanation-based_learning Explanation-based learning from Wikipedia]
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=References=  
 
=References=  
 
<references />
 
<references />
 
 
'''[[Main Page|Up one Level]]'''
 
'''[[Main Page|Up one Level]]'''
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[[Category:Videos]]

Revision as of 17:40, 27 June 2019

Home * Learning

Learning [1]

Learning,
the process of acquiring new knowledge which involves synthesizing different types of information. Machine learning as aspect of computer chess programming deals with algorithms that allow the program to change its behavior based on data, which for instance occurs during game playing against a variety of opponents considering the final outcome and/or the game record for instance as history score chart indexed by ply. Related to Machine learning is evolutionary computation and its sub-areas of genetic algorithms, and genetic programming, that mimics the process of natural evolution, as further mentioned in automated tuning. The process of learning often implies understanding, perception or reasoning. So called Rote learning avoids understanding and focuses on memorization. Inductive learning takes examples and generalizes rather than starting with existing knowledge. Deductive learning takes abstract concepts to make sense of examples [2].

Learning inside a Chess Program

Learning inside a chess program may address several disjoint issues. A persistent hash table remembers "important" positions from earlier games inside the search with its exact score [3]. Worse positions may be avoided in advance. Learning opening book moves, that is appending successful novelties or modify the probability of already stored moves from the book based on the outcome of a game [4]. Another application is learning evaluation weights of various features, f. i. piece- [5] or piece-square [6] values or mobility. Programs may also learn to control search [7] or time usage [8].

Learning Paradigms

There are three major learning paradigms, each corresponding to a particular abstract learning task. These are supervised learning, unsupervised learning and reinforcement learning. Usually any given type of neural network architecture can be employed in any of those tasks.

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 [9] .

Unsupervised Learning

Unsupervised machine learning seems much harder: the goal is to have the computer learn how to do something that we don't tell it how to do. The learner is given only unlabeled examples, f. i. a sequence of positions of a running game but the final result (still) unknown. A form of reinforcement learning can be used for unsupervised learning, where an agent bases its actions on the previous rewards and punishments without necessarily even learning any information about the exact ways that its actions affect the world. Clustering is another method of unsupervised learning.

Reinforcement Learning

see main page Reinforcement Learning

Reinforcement learning is defined not by characterizing learning methods, but by characterizing a learning problem. Reinforcement learning is learning what to do - how to map situations to actions - so as to maximize a numerical reward signal. The learner is not told which actions to take, as in most forms of machine learning, but instead must discover which actions yield the most reward by trying them. The reinforcement learning problem is deeply indebted to the idea of Markov decision processes (MDPs) from the field of optimal control.

Learning Topics

Programs

See also

Selected Publications

[10]

1940 ...

1950 ...

Claude Shannon, John McCarthy (eds.) (1956). Automata Studies. Annals of Mathematics Studies, No. 34
Alan Turing, Jack Copeland (editor) (2004). The Essential Turing, Seminal Writings in Computing, Logic, Philosophy, Artificial Intelligence, and Artificial Life plus The Secrets of Enigma. Oxford University Press, amazon, google books

1955 ...

Claude Shannon, John McCarthy (eds.) (1956). Automata Studies. Annals of Mathematics Studies, No. 34, pdf

1960 ...

1965 ...

1970 ...

1975 ...

  • Jacques Pitrat (1976). A Program to Learn to Play Chess. Pattern Recognition and Artificial Intelligence, pp. 399-419. Academic Press Ltd. London, UK. ISBN 0-12-170950-7.
  • 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. pdf
  • Ryszard Michalski, Pericles Negri (1977). An experiment on inductive learning in chess endgames. Machine Intelligence 8, 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.
  • Ross Quinlan (1979). Discovering Rules by Induction from Large Collections of Examples. Expert Systems in the Micro-electronic Age, pp. 168-201. Edinburgh University Press (Introducing ID3)

1980 ...

1985 ...

1986

1987

1988

1989

1990 ...

1991

1992

1993

1994

1995 ...

1996

1997

1998

Miroslav Kubat, Ivan Bratko, Ryszard Michalski (1998). A Review of Machine Learning Methods. pdf

1999

2000 ...

2001

2002

2003

2004

2005 ...

2006

2007

2008

2009

2010 ...

2011

2012

István Szita (2012). Reinforcement Learning in Games. Chapter 17

2013

2014

2015 ...

2016

2017

2018

Forum Posts

1998 ...

2000 ...

2005 ...

2010 ...

2015 ...

External Links

Machine Learning

AI

Learning I
Learning II

Chess

Supervised Learning

AdaBoost from Wikipedia

Unsupervised Learning

Reinforcement Learning

TD Learning

Statistics

Naive Bayes classifier from Wikipedia
Probabilistic classification from Wikipedia
Outline of regression analysis from Wikipedia
Linear regression from Wikipedia
Logistic regression from Wikipedia
Normal distribution from Wikipedia
Pseudorandom number generator from Wikipedia
Pseudo-random number sampling from Wikipedia
Statistical randomness from Wikipedia

Markov Models

NNs

ANNs

Topics

RNNs

Blogs

The Single Layer Perceptron
Hidden Neurons and Feature Space
Training Neural Networks Using Back Propagation in C#
Data Mining with Artificial Neural Networks (ANN)

Courses

References

  1. A depiction of the world's oldest continually operating university, the University of Bologna, Italy, by Laurentius de Voltolina, second half of 14th century, Learning from Wikipedia
  2. Inductive learning vs Deductive learning
  3. David Slate (1987). A Chess Program that uses its Transposition Table to Learn from Experience. ICCA Journal, Vol. 10, No. 2
  4. Robert Hyatt (1999). Book Learning - a Methodology to Tune an Opening Book Automatically. ICCA Journal, Vol. 22, No. 1
  5. Don Beal, Martin C. Smith (1997). Learning Piece Values Using Temporal Differences. ICCA Journal, Vol. 20, No. 3
  6. Don Beal, Martin C. Smith (1999). Learning Piece-Square Values using Temporal Differences. ICCA Journal, Vol. 22, No. 4
  7. Yngvi Björnsson, Tony Marsland (2001). Learning Search Control in Adversary Games. Advances in Computer Games 9, pdf
  8. Levente Kocsis, Jos Uiterwijk, Jaap van den Herik (2000). Learning Time Allocation using Neural Networks. CG 2000, postscript
  9. AI Horizon: Machine Learning, Part II: Supervised and Unsupervised Learning
  10. online papers from Machine Learning in Games by Jay Scott
  11. Rosenblatt's Contributions
  12. Ratio Club from Wikipedia
  13. Royal Radar Establishment from Wikipedia
  14. see Swap-off by Helmut Richter
  15. The abandonment of connectionism in 1969 - Wikipedia
  16. Frank Rosenblatt (1962). Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms. Spartan Books
  17. Long short term memory from Wikipedia
  18. Tsumego from Wikipedia
  19. Learnable Evolution Model from Wikipedia
  20. University of Bristol - Department of Computer Science - Technical Reports
  21. Generalized Hebbian Algorithm from Wikipedia
  22. Dap Hartmann (2010). Mimicking the Black Box - Genetically evolving evaluation functions and search algorithms. Review on Omid David's Ph.D. Thesis, ICGA Journal, Vol 33, No. 1
  23. Monte-Carlo Simulation Balancing - videolectures.net by David Silver
  24. MATLAB from Wikipedia
  25. Ms. Pac-Man from Wikipedia
  26. Demystifying Deep Reinforcement Learning by Tambet Matiisen, Nervana, December 21, 2015
  27. Patent US20150100530 - Methods and apparatus for reinforcement learning - Google Patents
  28. Jaap van den Herik wint Humies Award 2014 - LIACS - Leiden Institute of Advanced Computer Science
  29. 2048 (video game) from Wikipedia
  30. Teaching Deep Convolutional Neural Networks to Play Go by Hiroshi Yamashita, The Computer-go Archives, December 14, 2014
  31. Teaching Deep Convolutional Neural Networks to Play Go by Michel Van den Bergh, CCC, December 16, 2014
  32. Convolutional neural network from Wikipedia
  33. Best Paper Awards | TAAI 2014
  34. DeepChess: Another deep-learning based chess program by Matthew Lai, CCC, October 17, 2016
  35. ICANN 2016 | Recipients of the best paper awards
  36. Using GAN to play chess by Evgeniy Zheltonozhskiy, CCC, February 23, 2017
  37. Naive Bayes classifier from Wikipedia
  38. Amir Ban (2012). Automatic Learning of Evaluation, with Applications to Computer Chess. Discussion Paper 613, The Hebrew University of Jerusalem - Center for the Study of Rationality, Givat Ram
  39. Christopher Clark, Amos Storkey (2014). Teaching Deep Convolutional Neural Networks to Play Go. arXiv:1412.3409
  40. Chris J. Maddison, Aja Huang, Ilya Sutskever, David Silver (2014). Move Evaluation in Go Using Deep Convolutional Neural Networks. arXiv:1412.6564v1

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