Monte Carlo tree search (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Monte Carlo tree search" in English language version.

refsWebsite

Global rank English rank

17doi.org

2^nd place

12web.archive.org

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5psu.edu

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4semanticscholar.org

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3worldcat.org

5^th place

3arxiv.org

69^th place

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3hs-weingarten.de

low place

3free.fr

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2nih.gov

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2inria.fr

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2maastrichtuniversity.nl

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2umd.edu

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2ualberta.ca

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1harvard.edu

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1aigamedev.com

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1springer.com

274^th place

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1columbia.edu

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1ideanest.com

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1handle.net

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1informs.org

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1xmp.net

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1dcook.org

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1googleresearch.blogspot.com

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1youtube.com

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1zdnet.com

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1arimaa.com

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1nucl.ai

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1brad.ac.uk

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1uvt.nl

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1jeffbradberry.com

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1acm.org

1,185^th place

840^th place

1aaai.org

9,352^nd place

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1machinelearning.org

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1archive.org

6^th place

aaai.org

ojs.aaai.org

Ramanujan, Raghuram; Selman, Bart (March 2011). "Trade-Offs in Sampling-Based Adversarial Planning". Proceedings of the International Conference on Automated Planning and Scheduling. 21 (1): 202–209. doi:10.1609/icaps.v21i1.13472. S2CID 45147586.

acm.org

dl.acm.org

Ramanujan, Raghuram; Sabharwal, Ashish; Selman, Bart (May 2010). "On adversarial search spaces and sampling-based planning". ICAPS '10: Proceedings of the Twentieth International Conference on International Conference on Automated Planning and Scheduling. Icaps'10: 242–245.

aigamedev.com

"Monte-Carlo Tree Search in TOTAL WAR: ROME II's Campaign AI". AI Game Dev. Archived from the original on 13 March 2017. Retrieved 25 February 2017.

archive.org

Markus Enzenberger; Martin Müller (2010). "A Lock-free Multithreaded Monte-Carlo Tree Search Algorithm". In Jaap Van Den Herik; Pieter Spronck (eds.). Advances in Computer Games: 12th International Conference, ACG 2009, Pamplona, Spain, May 11–13, 2009, Revised Papers. Springer. pp. 14–20. CiteSeerX 10.1.1.161.1984. ISBN 978-3-642-12992-6.

arimaa.com

Tomáš Kozelek (2009). Methods of MCTS and the game Arimaa (PDF). Master's thesis, Charles University in Prague.

arxiv.org

Silver, David (2017). "Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm". arXiv:1712.01815v1 [cs.AI].
Kemmerling, Marco; Lütticke, Daniel; Schmitt, Robert H. (1 January 2024). "Beyond games: a systematic review of neural Monte Carlo tree search applications". Applied Intelligence. 54 (1): 1020–1046. arXiv:2303.08060. doi:10.1007/s10489-023-05240-w. ISSN 1573-7497.
Peres, Yuval; Schramm, Oded; Sheffield, Scott; Wilson, David B. (2006). "Random-Turn Hex and other selection games". arXiv:math/0508580.

bbc.com

"Google achieves AI 'breakthrough' by beating Go champion". BBC News. 27 January 2016.

brad.ac.uk

scim.brad.ac.uk

C.D. Ward; P.I. Cowling (2009). "Monte Carlo Search Applied to Card Selection in Magic: The Gathering" (PDF). CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games. IEEE Press. Archived from the original (PDF) on 2016-05-28.

columbia.edu

academiccommons.columbia.edu

Abramson, Bruce (1987). The Expected-Outcome Model of Two-Player Games (PDF). Technical report, Department of Computer Science, Columbia University. Retrieved 23 December 2013.

dcook.org

"The Shodan Go Bet". Retrieved 2012-05-02.

doi.org

Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.
Kemmerling, Marco; Lütticke, Daniel; Schmitt, Robert H. (1 January 2024). "Beyond games: a systematic review of neural Monte Carlo tree search applications". Applied Intelligence. 54 (1): 1020–1046. arXiv:2303.08060. doi:10.1007/s10489-023-05240-w. ISSN 1573-7497.
Nicholas, Metropolis; Stanislaw, Ulam (1949). "The monte carlo method". Journal of the American Statistical Association. 44 (247): 335–341. doi:10.1080/01621459.1949.10483310. PMID 18139350.
Chang, Hyeong Soo; Fu, Michael C.; Hu, Jiaqiao; Marcus, Steven I. (2005). "An Adaptive Sampling Algorithm for Solving Markov Decision Processes" (PDF). Operations Research. 53: 126–139. doi:10.1287/opre.1040.0145. hdl:1903/6264. Archived from the original (PDF) on 2021-04-20. Retrieved 2016-02-25.
Kocsis, Levente; Szepesvári, Csaba (2006). "Bandit based Monte-Carlo Planning". In Fürnkranz, Johannes; Scheffer, Tobias; Spiliopoulou, Myra (eds.). Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18–22, 2006, Proceedings. Lecture Notes in Computer Science. Vol. 4212. Springer. pp. 282–293. CiteSeerX 10.1.1.102.1296. doi:10.1007/11871842_29. ISBN 3-540-45375-X.
Chang-Shing Lee; Mei-Hui Wang; Guillaume Chaslot; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud; Shang-Rong Tsai; Shun-Chin Hsu; Tzung-Pei Hong (2009). "The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments" (PDF). IEEE Transactions on Computational Intelligence and AI in Games. 1 (1): 73–89. CiteSeerX 10.1.1.470.6018. doi:10.1109/tciaig.2009.2018703. S2CID 15266518.
Broderick Arneson; Ryan Hayward; Philip Henderson (June 2009). "MoHex Wins Hex Tournament" (PDF). ICGA Journal. 32 (2): 114–116. doi:10.3233/ICG-2009-32218.
Xiaocong Gan; Yun Bao; Zhangang Han (December 2011). "Real-Time Search Method in Nondeterministic Game – Ms. Pac-Man". ICGA Journal. 34 (4): 209–222. doi:10.3233/ICG-2011-34404.
Tom Pepels; Mark H. M. Winands; Marc Lanctot (September 2014). "Real-Time Monte Carlo Tree Search in Ms Pac-Man". IEEE Transactions on Computational Intelligence and AI in Games. 6 (3): 245–257. doi:10.1109/tciaig.2013.2291577.
Jonathan Rubin; Ian Watson (April 2011). "Computer poker: A review". Artificial Intelligence. 175 (5–6): 958–987. doi:10.1016/j.artint.2010.12.005.
G.M.J.B. Chaslot; M.H.M. Winands; J.W.H.M. Uiterwijk; H.J. van den Herik; B. Bouzy (2008). "Progressive Strategies for Monte-Carlo Tree Search" (PDF). New Mathematics and Natural Computation. 4 (3): 343–359. doi:10.1142/s1793005708001094.
Auer, Peter; Cesa-Bianchi, Nicolò; Fischer, Paul (2002). "Finite-time Analysis of the Multiarmed Bandit Problem". Machine Learning. 47 (2/3): 235–256. doi:10.1023/a:1013689704352. S2CID 207609497.
Browne, Cameron B.; Powley, Edward; Whitehouse, Daniel; Lucas, Simon M.; Cowling, Peter I.; Rohlfshagen, Philipp; Tavener, Stephen; Perez, Diego; Samothrakis, Spyridon; Colton, Simon (2012). "A Survey of Monte Carlo Tree Search Methods". IEEE Transactions on Computational Intelligence and AI in Games. 4 (1): 1–43. doi:10.1109/tciaig.2012.2186810. ISSN 1943-068X.
Althöfer, Ingo (2012). "On Board-Filling Games with Random-Turn Order and Monte Carlo Perfectness". Advances in Computer Games. Lecture Notes in Computer Science. Vol. 7168. pp. 258–269. doi:10.1007/978-3-642-31866-5_22. ISBN 978-3-642-31865-8.
Ramanujan, Raghuram; Selman, Bart (March 2011). "Trade-Offs in Sampling-Based Adversarial Planning". Proceedings of the International Conference on Automated Planning and Scheduling. 21 (1): 202–209. doi:10.1609/icaps.v21i1.13472. S2CID 45147586.
Drake, Peter (December 2009). "The Last-Good-Reply Policy for Monte-Carlo Go". ICGA Journal. 32 (4): 221–227. doi:10.3233/ICG-2009-32404.

dx.doi.org

Browne, Cameron B.; Powley, Edward; Whitehouse, Daniel; Lucas, Simon M.; Cowling, Peter I.; Rohlfshagen, Philipp; Tavener, Stephen; Perez, Diego; Samothrakis, Spyridon; Colton, Simon (2012). "A Survey of Monte Carlo Tree Search Methods". IEEE Transactions on Computational Intelligence and AI in Games. 4 (1): 1–43. doi:10.1109/tciaig.2012.2186810. ISSN 1943-068X.

ewalds.ca

havannah.ewalds.ca

Timo Ewalds (2011). Playing and Solving Havannah (PDF). Master's thesis, University of Alberta.

free.fr

remi.coulom.free.fr

Rémi Coulom (2008). "The Monte-Carlo Revolution in Go" (PDF). Japanese-French Frontiers of Science Symposium.
Rémi Coulom. "CLOP: Confident Local Optimization for Noisy Black-Box Parameter Tuning". ACG 2011: Advances in Computer Games 13 Conference, Tilburg, the Netherlands, November 20–22.

pug.raph.free.fr

Markus Enzenberger; Martin Mūller (2008). Fuego – An Open-Source Framework for Board Games and Go Engine Based on Monte Carlo Tree Search (PDF). Technical report, University of Alberta.

googleresearch.blogspot.com

"Research Blog: AlphaGo: Mastering the ancient game of Go with Machine Learning". Google Research Blog. 27 January 2016.

handle.net

hdl.handle.net

Chang, Hyeong Soo; Fu, Michael C.; Hu, Jiaqiao; Marcus, Steven I. (2005). "An Adaptive Sampling Algorithm for Solving Markov Decision Processes" (PDF). Operations Research. 53: 126–139. doi:10.1287/opre.1040.0145. hdl:1903/6264. Archived from the original (PDF) on 2021-04-20. Retrieved 2016-02-25.

harvard.edu

ui.adsabs.harvard.edu

Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.

hs-weingarten.de

Wolfgang Ertel; Johann Schumann; Christian Suttner (1989). "Learning Heuristics for a Theorem Prover using Back Propagation.". In J. Retti; K. Leidlmair (eds.). 5. Österreichische Artificial-Intelligence-Tagung. Informatik-Fachberichte 208, pp. 87-95. Springer. Archived from the original on 2021-04-15. Retrieved 2016-08-14.
Christian Suttner; Wolfgang Ertel (1990). "Automatic Acquisition of Search Guiding Heuristics.". CADE90, 10th Int. Conf. on Automated Deduction.pp. 470-484. LNAI 449. Springer. Archived from the original on 2021-04-15. Retrieved 2016-08-14.
Christian Suttner; Wolfgang Ertel (1991). "Using Back-Propagation Networks for Guiding the Search of a Theorem Prover". Journal of Neural Networks Research & Applications. 2 (1): 3–16. Archived from the original on 2021-04-15. Retrieved 2016-08-14.

ideanest.com

Brügmann, Bernd (1993). Monte Carlo Go (PDF). Technical report, Department of Physics, Syracuse University.

informs.org

Hyeong Soo Chang; Michael Fu; Jiaqiao Hu; Steven I. Marcus (2016). "Google DeepMind's Alphago: O.R.'s unheralded role in the path-breaking achievement". OR/MS Today. 45 (5): 24–29.

inria.fr

hal.inria.fr

Sylvain Gelly; Yizao Wang; Rémi Munos; Olivier Teytaud (November 2006). Modification of UCT with Patterns in Monte-Carlo Go (PDF). Technical report, INRIA.
Chang-Shing Lee; Mei-Hui Wang; Guillaume Chaslot; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud; Shang-Rong Tsai; Shun-Chin Hsu; Tzung-Pei Hong (2009). "The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments" (PDF). IEEE Transactions on Computational Intelligence and AI in Games. 1 (1): 73–89. CiteSeerX 10.1.1.470.6018. doi:10.1109/tciaig.2009.2018703. S2CID 15266518.

jeffbradberry.com

Bradberry, Jeff (2015-09-07). "Introduction to Monte Carlo Tree Search".

maastrichtuniversity.nl

dke.maastrichtuniversity.nl

G.M.J.B. Chaslot; M.H.M. Winands; J.W.H.M. Uiterwijk; H.J. van den Herik; B. Bouzy (2008). "Progressive Strategies for Monte-Carlo Tree Search" (PDF). New Mathematics and Natural Computation. 4 (3): 343–359. doi:10.1142/s1793005708001094.
Guillaume M.J-B. Chaslot, Mark H.M. Winands, Jaap van den Herik (2008). "Parallel Monte-Carlo Tree Search" (PDF). Computers and Games, 6th International Conference, CG 2008, Beijing, China, September 29 – October 1, 2008. Proceedings. H. Jaap van den Herik, Xinhe Xu, Zongmin Ma, Mark H. M. Winands (eds.). Springer. pp. 60–71. ISBN 978-3-540-87607-6.{{cite book}}: CS1 maint: multiple names: authors list (link)

machinelearning.org

Gelly, Sylvain; Silver, David (2007). "Combining Online and Offline Knowledge in UCT" (PDF). Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20–24, 2007. Zoubin Ghahramani (ed.). ACM. pp. 273–280. ISBN 978-1-59593-793-3. Archived from the original (PDF) on 2017-08-28.

nih.gov

pubmed.ncbi.nlm.nih.gov

Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.
Nicholas, Metropolis; Stanislaw, Ulam (1949). "The monte carlo method". Journal of the American Statistical Association. 44 (247): 335–341. doi:10.1080/01621459.1949.10483310. PMID 18139350.

nucl.ai

archives.nucl.ai

Mountain, Gwaredd (2015). "Tactical Planning and Real-time MCTS in Fable Legends". Archived from the original on 2019-06-08. Retrieved 2019-06-08. .. we implemented a simulation based approach, which involved modelling the game play and using MCTS to search the potential plan space. Overall this worked well, ...

psu.edu

citeseerx.ist.psu.edu

Rémi Coulom (2007). "Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search". Computers and Games, 5th International Conference, CG 2006, Turin, Italy, May 29–31, 2006. Revised Papers. H. Jaap van den Herik, Paolo Ciancarini, H. H. L. M. Donkers (eds.). Springer. pp. 72–83. CiteSeerX 10.1.1.81.6817. ISBN 978-3-540-75537-1.
Kocsis, Levente; Szepesvári, Csaba (2006). "Bandit based Monte-Carlo Planning". In Fürnkranz, Johannes; Scheffer, Tobias; Spiliopoulou, Myra (eds.). Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18–22, 2006, Proceedings. Lecture Notes in Computer Science. Vol. 4212. Springer. pp. 282–293. CiteSeerX 10.1.1.102.1296. doi:10.1007/11871842_29. ISBN 3-540-45375-X.
Chang-Shing Lee; Mei-Hui Wang; Guillaume Chaslot; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud; Shang-Rong Tsai; Shun-Chin Hsu; Tzung-Pei Hong (2009). "The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments" (PDF). IEEE Transactions on Computational Intelligence and AI in Games. 1 (1): 73–89. CiteSeerX 10.1.1.470.6018. doi:10.1109/tciaig.2009.2018703. S2CID 15266518.
Michael Buro; Jeffrey Richard Long; Timothy Furtak; Nathan R. Sturtevant (2009). "Improving State Evaluation, Inference, and Search in Trick-Based Card Games". IJCAI 2009, Proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, USA, July 11–17, 2009. Craig Boutilier (ed.). pp. 1407–1413. CiteSeerX 10.1.1.150.3077.
Markus Enzenberger; Martin Müller (2010). "A Lock-free Multithreaded Monte-Carlo Tree Search Algorithm". In Jaap Van Den Herik; Pieter Spronck (eds.). Advances in Computer Games: 12th International Conference, ACG 2009, Pamplona, Spain, May 11–13, 2009, Revised Papers. Springer. pp. 14–20. CiteSeerX 10.1.1.161.1984. ISBN 978-3-642-12992-6.

semanticscholar.org

api.semanticscholar.org

Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.
Chang-Shing Lee; Mei-Hui Wang; Guillaume Chaslot; Jean-Baptiste Hoock; Arpad Rimmel; Olivier Teytaud; Shang-Rong Tsai; Shun-Chin Hsu; Tzung-Pei Hong (2009). "The Computational Intelligence of MoGo Revealed in Taiwan's Computer Go Tournaments" (PDF). IEEE Transactions on Computational Intelligence and AI in Games. 1 (1): 73–89. CiteSeerX 10.1.1.470.6018. doi:10.1109/tciaig.2009.2018703. S2CID 15266518.
Auer, Peter; Cesa-Bianchi, Nicolò; Fischer, Paul (2002). "Finite-time Analysis of the Multiarmed Bandit Problem". Machine Learning. 47 (2/3): 235–256. doi:10.1023/a:1013689704352. S2CID 207609497.
Ramanujan, Raghuram; Selman, Bart (March 2011). "Trade-Offs in Sampling-Based Adversarial Planning". Proceedings of the International Conference on Automated Planning and Scheduling. 21 (1): 202–209. doi:10.1609/icaps.v21i1.13472. S2CID 45147586.

springer.com

link.springer.com

Kemmerling, Marco; Lütticke, Daniel; Schmitt, Robert H. (1 January 2024). "Beyond games: a systematic review of neural Monte Carlo tree search applications". Applied Intelligence. 54 (1): 1020–1046. arXiv:2303.08060. doi:10.1007/s10489-023-05240-w. ISSN 1573-7497.

ualberta.ca

webdocs.cs.ualberta.ca

Broderick Arneson; Ryan Hayward; Philip Henderson (June 2009). "MoHex Wins Hex Tournament" (PDF). ICGA Journal. 32 (2): 114–116. doi:10.3233/ICG-2009-32218.

papersdb.cs.ualberta.ca

David Silver (2009). Reinforcement Learning and Simulation-Based Search in Computer Go (PDF). PhD thesis, University of Alberta.

umd.edu

cs.umd.edu

Rajkumar, Prahalad. "A Survey of Monte-Carlo Techniques in Games" (PDF). cs.umd.edu. Archived (PDF) from the original on 2023-04-07.

scholar.rhsmith.umd.edu

Chang, Hyeong Soo; Fu, Michael C.; Hu, Jiaqiao; Marcus, Steven I. (2005). "An Adaptive Sampling Algorithm for Solving Markov Decision Processes" (PDF). Operations Research. 53: 126–139. doi:10.1287/opre.1040.0145. hdl:1903/6264. Archived from the original (PDF) on 2021-04-20. Retrieved 2016-02-25.

uvt.nl

ticc.uvt.nl

István Szita; Guillaume Chaslot; Pieter Spronck (2010). "Monte-Carlo Tree Search in Settlers of Catan" (PDF). In Jaap Van Den Herik; Pieter Spronck (eds.). Advances in Computer Games, 12th International Conference, ACG 2009, Pamplona, Spain, May 11–13, 2009. Revised Papers. Springer. pp. 21–32. ISBN 978-3-642-12992-6. Archived from the original (PDF) on 2016-03-04. Retrieved 2015-11-30.

web.archive.org

Rajkumar, Prahalad. "A Survey of Monte-Carlo Techniques in Games" (PDF). cs.umd.edu. Archived (PDF) from the original on 2023-04-07.
"Monte-Carlo Tree Search in TOTAL WAR: ROME II's Campaign AI". AI Game Dev. Archived from the original on 13 March 2017. Retrieved 25 February 2017.
Wolfgang Ertel; Johann Schumann; Christian Suttner (1989). "Learning Heuristics for a Theorem Prover using Back Propagation.". In J. Retti; K. Leidlmair (eds.). 5. Österreichische Artificial-Intelligence-Tagung. Informatik-Fachberichte 208, pp. 87-95. Springer. Archived from the original on 2021-04-15. Retrieved 2016-08-14.
Christian Suttner; Wolfgang Ertel (1990). "Automatic Acquisition of Search Guiding Heuristics.". CADE90, 10th Int. Conf. on Automated Deduction.pp. 470-484. LNAI 449. Springer. Archived from the original on 2021-04-15. Retrieved 2016-08-14.
Christian Suttner; Wolfgang Ertel (1991). "Using Back-Propagation Networks for Guiding the Search of a Theorem Prover". Journal of Neural Networks Research & Applications. 2 (1): 3–16. Archived from the original on 2021-04-15. Retrieved 2016-08-14.
Chang, Hyeong Soo; Fu, Michael C.; Hu, Jiaqiao; Marcus, Steven I. (2005). "An Adaptive Sampling Algorithm for Solving Markov Decision Processes" (PDF). Operations Research. 53: 126–139. doi:10.1287/opre.1040.0145. hdl:1903/6264. Archived from the original (PDF) on 2021-04-20. Retrieved 2016-02-25.
"Sensei's Library: KGSBotRatings" (PDF). Archived from the original on 2009-06-25. Retrieved 2012-05-03.
Mountain, Gwaredd (2015). "Tactical Planning and Real-time MCTS in Fable Legends". Archived from the original on 2019-06-08. Retrieved 2019-06-08. .. we implemented a simulation based approach, which involved modelling the game play and using MCTS to search the potential plan space. Overall this worked well, ...
C.D. Ward; P.I. Cowling (2009). "Monte Carlo Search Applied to Card Selection in Magic: The Gathering" (PDF). CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games. IEEE Press. Archived from the original (PDF) on 2016-05-28.
István Szita; Guillaume Chaslot; Pieter Spronck (2010). "Monte-Carlo Tree Search in Settlers of Catan" (PDF). In Jaap Van Den Herik; Pieter Spronck (eds.). Advances in Computer Games, 12th International Conference, ACG 2009, Pamplona, Spain, May 11–13, 2009. Revised Papers. Springer. pp. 21–32. ISBN 978-3-642-12992-6. Archived from the original (PDF) on 2016-03-04. Retrieved 2015-11-30.
"Lee Sedol defeats AlphaGo in masterful comeback - Game 4". Go Game Guru. Archived from the original on 2016-11-16. Retrieved 2017-07-04.
Gelly, Sylvain; Silver, David (2007). "Combining Online and Offline Knowledge in UCT" (PDF). Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20–24, 2007. Zoubin Ghahramani (ed.). ACM. pp. 273–280. ISBN 978-1-59593-793-3. Archived from the original (PDF) on 2017-08-28.

worldcat.org

search.worldcat.org

Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.
Kemmerling, Marco; Lütticke, Daniel; Schmitt, Robert H. (1 January 2024). "Beyond games: a systematic review of neural Monte Carlo tree search applications". Applied Intelligence. 54 (1): 1020–1046. arXiv:2303.08060. doi:10.1007/s10489-023-05240-w. ISSN 1573-7497.
Browne, Cameron B.; Powley, Edward; Whitehouse, Daniel; Lucas, Simon M.; Cowling, Peter I.; Rohlfshagen, Philipp; Tavener, Stephen; Perez, Diego; Samothrakis, Spyridon; Colton, Simon (2012). "A Survey of Monte Carlo Tree Search Methods". IEEE Transactions on Computational Intelligence and AI in Games. 4 (1): 1–43. doi:10.1109/tciaig.2012.2186810. ISSN 1943-068X.

xmp.net

senseis.xmp.net

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"Match 1 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo". Youtube. 9 March 2016.

zdnet.com

"Google AlphaGo AI clean sweeps European Go champion". ZDNet. 28 January 2016.