Search results

* [[:Category:MCTS]]

* [[Monte-Carlo Tree Search|MCTS]] - Monte-Carlo Tree Search

* [https://groups.google.com/d/msg/fishcooking/rMCfc8zMerc/F01WuNtDCgAJ MCTS wrapper for StockFish] by [[Jonathan Baxter]], [[Computer Chess Forums|Fish

...learning]] along with [[Monte-Carlo Tree Search|Monte-Carlo tree search]] (MCTS) techniques of [[AlphaZero]] as described in [[DeepMind|DeepMind's]] 2017 a ...xecutable, the actual chess engine, performs the [[Monte-Carlo Tree Search|MCTS]] and reads the self-taught [[Neural Networks#Convolutional|CNN]], which we

'''Monte Carlo Tree Search''', (Monte-Carlo Tree Search, MCTS)<br/> ...in Games]], Vol. 2, No. 4, [http://webdocs.cs.ualberta.ca/~hayward/papers/mcts-hex.pdf pdf]</ref>, [[Checkers]] <ref>[http://www.talkchess.com/forum/viewt

...63 Pruning Game Tree by Rollouts]''. [[AAAI]] » [[Monte-Carlo Tree Search|MCTS]], [[SSS* and Dual*#SSStarandDualStarAsMT|MT-SSS*]], [[Bojun Huang#Rollout| ...pter/10.1007/978-3-319-57969-6_5 A Rollout-Based Search Algorithm Unifying MCTS and Alpha-Beta]''. [https://link.springer.com/book/10.1007%2F978-3-319-5796

...2019 » [[Principal Variation#MultiPV|MultiPV]], [[Monte-Carlo Tree Search|MCTS]]

...org/abs/1409.4297 CoRR abs/1409.4297] » [[Go]], [[Monte-Carlo Tree Search|MCTS]] .../abs/1507.04383 CoRR abs/1507.04383] » [[Hex]], [[Monte-Carlo Tree Search|MCTS]], [[Parallel Search]], [[x86-64]]

...[SSS* and Dual*#SSStarandDualStarAsMT|MT-SSS*]], [[Monte-Carlo Tree Search|MCTS]] <ref>[http://www.talkchess.com/forum/viewtopic.php?t=66280&start=67 Re: A

...z]] ('''2011'''). ''UCT-Treesplit - Parallel MCTS on Distributed Memory''. MCTS Workshop, Freiburg, Germany, [http://www.cs.uni-paderborn.de/fileadmin/Info ...rg/abs/1409.4297 CoRR abs/1409.4297] » [[Go]], [[Monte-Carlo Tree Search|MCTS]], [[x86-64]]

...Monte Carlo tree search''. » [[Deep Learning]], [[Monte-Carlo Tree Search|MCTS]] ...Carlo tree search?'' [[CG 2018]] » [[Othello]], [[Monte-Carlo Tree Search|MCTS]]

...). ''[http://www.aifactory.co.uk/newsletter/2011_02_mcts_static.htm Mixing MCTS with Conventional Static Evaluation]''. [[AI Factory]], Winter 2011 » [[Mo

...[[Jr-Chang Chen]] ('''2015'''). ''Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program''. [[Advances in Computer Games 14]]

* [http://www.talkchess.com/forum/viewtopic.php?t=41730 MCTS without random playout?] by [[Antonio Torrecillas]], [[CCC]], January 01, 2

* [http://talkchess.com/forum3/viewtopic.php?t=74891 "New" Engines (lc0, MCTS, SFNNUE) and suitable GUIs] by Hamster, [[CCC]], August 25, 2020

...en]] ('''2014'''). ''Performance analysis of a 240 thread tournament level MCTS Go program on the Intel Xeon Phi''. [http://arxiv.org/abs/1409.4297 CoRR ab .../abs/1507.04383 CoRR abs/1507.04383] » [[Hex]], [[Monte-Carlo Tree Search|MCTS]], [[Parallel Search]]

...://arxiv.org/abs/1802.05944 arXiv:1802.05944] » [[Monte-Carlo Tree Search|MCTS]], [[General Game Playing]]

...[[Neural Networks#Deep|Deep Learning]], [[Go]], [[Monte-Carlo Tree Search|MCTS]] * [http://www.talkchess.com/forum3/viewtopic.php?f=7&t=71301 A question to MCTS + NN experts] by [[Maksim Korzh]], [[CCC]], July 17, 2019 » [[Monte-Carlo

...11'''). ''[http://link.springer.com/chapter/10.1007/978-3-642-31866-5_5 An MCTS Program to Play EinStein Würfelt Nicht!]'' ...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''.

* [[Richard J. Lorentz]] ('''2015'''). ''Early Playout Termination in MCTS''. [[Advances in Computer Games 14]] ...[[Jr-Chang Chen]] ('''2015'''). ''Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program''. [[Advances in Computer Games 14]]

...Müller]], [[Jakub Pawlewicz]] ('''2013'''). ''MoHex 2.0: a pattern-based MCTS Hex player''. [[CG 2013]], [https://webdocs.cs.ualberta.ca/~hayward/papers/

...s://arxiv.org/abs/1607.08100 arXiv:1607.0810] » [[Monte-Carlo Tree Search|MCTS]]

* [[Tomas Kozelek]] ('''2009'''). ''Methods of MCTS and the game Arimaa''. Master's thesis, [http://arimaa.com/arimaa/papers/To * [[Tomáš Jakl]] ('''2011'''). ''Arimaa Challenge – Comparison Study of MCTS versus Alpha-Beta Methods''. B.Sc. thesis, [https://en.wikipedia.org/wiki/C

...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''. [[Advances in Computer Games 13]] ...//arxiv.org/abs/1409.4297 CoRR abs/1409.4297] » [[Monte-Carlo Tree Search|MCTS]], [[Parallel Search]], [[x86-64]]

| [[Monte-Carlo Tree Search|MCTS]], [[UCT|RAVE UCT]] | [[Monte-Carlo Tree Search|MCTS]], [[UCT]], Solver

...rained_models/writeup.pdf pdf] » [[AlphaZero]], [[Monte-Carlo Tree Search|MCTS]], [[Deep Learning]] <ref>[https://github.com/suragnair/alpha-zero-general

...11'''). ''[http://link.springer.com/chapter/10.1007/978-3-642-31866-5_5 An MCTS Program to Play EinStein Würfelt Nicht!]'' [[Advances in Computer Games 13

* [[Nicolas Jouandeau]], [[Tristan Cazenave]] ('''2014'''). ''Small and Large MCTS Playouts applied to Chinese Dark Chess Stochastic Game''. [[ECAI CGW 2014]]

...://arxiv.org/abs/1802.05944 arXiv:1802.05944] » [[Monte-Carlo Tree Search|MCTS]], [[Reinforcement Learning]]

...[[Jr-Chang Chen]] ('''2015'''). ''Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program''. [[Advances in Computer Games 14]]

: [[Nicolas Jouandeau]], [[Tristan Cazenave]] ('''2014'''). ''Small and Large MCTS Playouts applied to Chinese Dark Chess Stochastic Game''. [[ECAI CGW 2014]]

...dural content generation in creative domains, to investigate ways in which MCTS - typically used for move planning in games - can instead be harnessed to a

Most contemporary implementations of MCTS are based on some variant of UCT <ref>[https://en.wikipedia.org/wiki/Monte_ ...<ref>[http://www.talkchess.com/forum/viewtopic.php?t=66125 Search traps in MCTS and chess] by [[Daniel Shawul]], [[CCC]], December 25, 2017</ref>

...nce], Vol. 84, No 1-2</ref>, one distinction between the two might be that MCTS uses usually win/draw/loss scores and Best-First a score from a heuristic [ ...63 Pruning Game Tree by Rollouts]''. [[AAAI]] » [[Monte-Carlo Tree Search|MCTS]], [[SSS* and Dual*#SSStarandDualStarAsMT|MT-SSS*]], [[Bojun Huang#Rollout|

...pter/10.1007/978-3-319-57969-6_5 A Rollout-Based Search Algorithm Unifying MCTS and Alpha-Beta]''. [https://link.springer.com/book/10.1007%2F978-3-319-5796 ...63 Pruning Game Tree by Rollouts]''. [[AAAI]] » [[Monte-Carlo Tree Search|MCTS]], [[SSS* and Dual*#SSStarandDualStarAsMT|MT-SSS*]] <ref>[http://www.talkch

...11'''). ''[http://link.springer.com/chapter/10.1007/978-3-642-31866-5_5 An MCTS Program to Play EinStein Würfelt Nicht!]'' [[Advances in Computer Games 13 * [[Richard J. Lorentz]] ('''2015'''). ''Early Playout Termination in MCTS''. [[Advances in Computer Games 14]]

...in Games]], Vol. 2, No. 4, [http://webdocs.cs.ualberta.ca/~hayward/papers/mcts-hex.pdf pdf]</ref>. ...n Games]], Vol. 2, No. 4, [http://webdocs.cs.ualberta.ca/%7Ehayward/papers/mcts-hex.pdf pdf]

...Müller]], [[Jakub Pawlewicz]] ('''2013'''). ''MoHex 2.0: a pattern-based MCTS Hex player''. [[CG 2013]], [https://webdocs.cs.ualberta.ca/~hayward/papers/

...MHex · GitHub]</ref>. It was built by a group of students and is based on MCTS with [[UCT|RAVE UCT]]. Along with [[Łukasz Lew]], he applied proof-number ...Müller]], [[Jakub Pawlewicz]] ('''2013'''). ''MoHex 2.0: a pattern-based MCTS Hex player''. [[CG 2013]], [https://webdocs.cs.ualberta.ca/~hayward/papers/

...org/abs/1409.4297 CoRR abs/1409.4297] » [[Go]], [[Monte-Carlo Tree Search|MCTS]] .../abs/1507.04383 CoRR abs/1507.04383] » [[Hex]], [[Monte-Carlo Tree Search|MCTS]], [[Parallel Search]], [[x86-64]]

...org/abs/1409.4297 CoRR abs/1409.4297] » [[Go]], [[Monte-Carlo Tree Search|MCTS]] .../abs/1507.04383 CoRR abs/1507.04383] » [[Hex]], [[Monte-Carlo Tree Search|MCTS]], [[Parallel Search]], [[x86-64]]

....org/abs/1512.03375 arXiv:1512.03375] » [[Go]], [[Monte-Carlo Tree Search|MCTS]] ...rained_models/writeup.pdf pdf] » [[AlphaZero]], [[Monte-Carlo Tree Search|MCTS]], [[Othello]] <ref>[https://github.com/suragnair/alpha-zero-general GitHub

...'2011'''). ''[http://link.springer.com/chapter/10.1007/978-3-642-31866-5_9 MCTS Experiments on the Voronoi Game]''. [[Advances in Computer Games 13]]

...). ''[http://www.aifactory.co.uk/newsletter/2011_02_mcts_static.htm Mixing MCTS with Conventional Static Evaluation: Experiments and shortcuts en-route to ...ctory.co.uk/newsletter/2013_02_unknown_mcts.htm Searching the Unknown with MCTS]''. [[AI Factory]], Winter 2013 » [[Monte-Carlo Tree Search]]

...<ref>[http://www.talkchess.com/forum/viewtopic.php?t=66125 Search traps in MCTS and chess] by [[Daniel Shawul]], [[CCC]], December 25, 2017</ref>

...<ref>[http://www.talkchess.com/forum/viewtopic.php?t=66125 Search traps in MCTS and chess] by [[Daniel Shawul]], [[CCC]], December 25, 2017</ref>

...<ref>[http://www.talkchess.com/forum/viewtopic.php?t=66125 Search traps in MCTS and chess] by [[Daniel Shawul]], [[CCC]], December 25, 2017</ref>

...z]] ('''2011'''). ''UCT-Treesplit - Parallel MCTS on Distributed Memory''. MCTS Workshop, Freiburg, Germany, [http://www.cs.uni-paderborn.de/fileadmin/Info

...[[Jr-Chang Chen]] ('''2015'''). ''Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program''. [[Advances in Computer Games 14]]

...[[Jr-Chang Chen]] ('''2015'''). ''Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program''. [[Advances in Computer Games 14]]

...[[Jr-Chang Chen]] ('''2015'''). ''Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program''. [[Advances in Computer Games 14]]

...ical optimization], [[Parallel Search|parallel]] [[Monte-Carlo Tree Search|MCTS]], and recently [[Go#CNN|DCNN]] <ref>[https://groups.google.com/d/msg/compu

...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''. [[Advances in Computer Games 13]] ...[[Jr-Chang Chen]] ('''2015'''). ''Strength Improvement and Analysis for an MCTS-Based Chinese Dark Chess Program''. [[Advances in Computer Games 14]]

...bfb6ecc6fb5afb684df03d7220c46ebdbf4e.pdf pdf] » [[Monte-Carlo Tree Search|MCTS]], [[UCT]], [[Reinforcement Learning]] ...[http://proceedings.mlr.press/ PMLR], Vol. 24 » [[Monte-Carlo Tree Search|MCTS]], [[UCT]]

...[http://proceedings.mlr.press/ PMLR], Vol. 24 » [[Monte-Carlo Tree Search|MCTS]], [[UCT]]

==MCTS== ...and [[ABDADA]] like BUSY flag for alpha-beta rollouts. ABDADA and parallel MCTS from the [[Go]] world are very similar in nature <ref>[http://www.talkchess

...]] <ref> [http://rybkaforum.net/cgi-bin/rybkaforum/topic_show.pl?tid=32429 MCTS weakness wrt AB (via Daniel Shawul)] by [[Chris Whittington]], [[Computer C

* [http://www.talkchess.com/forum/viewtopic.php?t=65964 Nebiyu-MCTS vs TSCP 1-0] by [[Daniel Shawul]], [[CCC]], December 10, 2017 » [[UCT]] [[Category:MCTS]]

...valuation|evaluation]] function in the rollout phase and move selection of MCTS - with encouraging results in the domains of [[Othello]] and [https://en.wi ...pter/10.1007/978-3-319-57969-6_5 A Rollout-Based Search Algorithm Unifying MCTS and Alpha-Beta]''. [https://link.springer.com/book/10.1007%2F978-3-319-5796

...<ref>[https://groups.google.com/d/msg/fishcooking/rMCfc8zMerc/F01WuNtDCgAJ MCTS wrapper for StockFish] by [[Jonathan Baxter]], [[Computer Chess Forums|Fish * [https://groups.google.com/d/msg/fishcooking/rMCfc8zMerc/F01WuNtDCgAJ MCTS wrapper for StockFish] by [[Jonathan Baxter]], [[Computer Chess Forums|Fish

...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''. [[Advances in Computer Games 13]] ...s://arxiv.org/abs/1607.08100 arXiv:1607.0810] » [[Monte-Carlo Tree Search|MCTS]]

...learning]] along with [[Monte-Carlo Tree Search|Monte-Carlo tree search]] (MCTS) techniques of [[AlphaZero]] as described in [[DeepMind|DeepMind's]] 2017 a

...nsei's Library: Zen (go program)]</ref> applying [[Monte-Carlo Tree Search|MCTS]] using big patterns and [[Root|root]] [[Parallel Search|parallelization]]

...aGo Zero paper]</ref>, a Go playing entity using [[Monte-Carlo Tree Search|MCTS]] (but without Monte Carlo playouts) and a [[Neural Networks#Deep|deep]] [[

...[Chris Whittington]], [[CCC]], April 28, 2019 » [[Monte-Carlo Tree Search|MCTS]], [[Deep Learning]]

...). ''[http://www.aifactory.co.uk/newsletter/2011_02_mcts_static.htm Mixing MCTS with Conventional Static Evaluation: Experiments and shortcuts en-route to ...ctory.co.uk/newsletter/2013_02_unknown_mcts.htm Searching the Unknown with MCTS]''. [[AI Factory]], Winter 2013 » [[Monte-Carlo Tree Search]]

...?id=528 MC_ark], a Go playing program performing [[Monte-Carlo Tree Search|MCTS]], inspired by [[Rémi Coulom|Rémi Coulom's]] [[CGW 2007]] paper ''Computi

...ombining [[Deep Learning|Deep learning]] with [[Monte-Carlo Tree Search]] (MCTS) <ref>[[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioan ...nce trained, these network is combined with a [[Monte-Carlo Tree Search]] (MCTS) using the policy to narrow down the search to high ­probability moves, an

[[Category:MCTS]]

* [[Jacek Mańdziuk]] ('''2018'''). ''MCTS/UCT in Solving Real-Life Problems''. [https://www.springer.com/us/book/9783

...proved engine, Komodo 12 features an optional [[Monte-Carlo Tree Search]] (MCTS), the release likely influenced by the [[AlphaZero]] hype. ....talkchess.com/forum3/viewtopic.php?f=2&t=67441&start=25 Re: Komodo 12 and MCTS] by [[Mark Lefler]], [[CCC]], May 14, 2018</ref>

...Müller]], [[Jakub Pawlewicz]] ('''2013'''). ''MoHex 2.0: a pattern-based MCTS Hex player''. [[CG 2013]]

#REDIRECT [[Komodo#MCTS]]

* [http://www.talkchess.com/forum3/viewtopic.php?f=7&t=69612 MCTS: How to deal with extreme imbalances] by [[Alexandru Mosoi]], [[CCC]], Janu

* [http://www.talkchess.com/forum3/viewtopic.php?f=7&t=69612 MCTS: How to deal with extreme imbalances] by [[Alexandru Mosoi]], [[CCC]], Janu

...st-First|Best-first]] [[Monte-Carlo Tree Search|Monte-Carlo Tree Search]] (MCTS) with [[Deep Learning|deep learning]] methodology will work with GPU archit ...fecting game playing programs combining CNN with [[Monte-Carlo Tree Search|MCTS]], as pioneered by [[Google]] [[DeepMind|DeepMind's]] [[AlphaGo]] and [[Alp

* [http://www.talkchess.com/forum3/viewtopic.php?f=7&t=67235&start=10 Re: MCTS beginner questions] by [[Brian Richardson]], [[CCC]], April 27, 2018

* [http://www.talkchess.com/forum/viewtopic.php?t=41730 MCTS without random playout?] by [[Antonio Torrecillas]], [[CCC]], January 01, 2

...earch algorithm <ref>[http://www.talkchess.com/forum/viewtopic.php?t=41730 MCTS without random playout?] by [[Antonio Torrecillas]], [[CCC]], January 01, 2 ...ach_game=1&eng=Rocinante%202.0%2064-bit%20%28mcts%29 Rocinante 2.0 64-bit (mcts)] in [[CCRL|CCRL 40/4]]

...jun Huang#Rollout|Rollout Paradigm]] and further [[Monte-Carlo_Tree_Search|MCTS]]-minimax hybrids share the same idea, to combine Best-First with Depth-Fir * [http://www.talkchess.com/forum/viewtopic.php?t=41730 MCTS without random playout?] by [[Antonio Torrecillas]], [[CCC]], January 01, 2

...ks on [[Monte-Carlo Tree Search]], [[UCT]], and [[Parallel Search|parallel MCTS]]. ...org/abs/1409.4297 CoRR abs/1409.4297] » [[Go]], [[Monte-Carlo Tree Search|MCTS]]

...://arxiv.org/abs/1802.05944 arXiv:1802.05944] » [[Monte-Carlo Tree Search|MCTS]], [[Reinforcement Learning]]

...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''. [[Advances in Computer Games 13]]

...ture_University OPU], for example, the number of [[Monte-Carlo Tree Search|MCTS]] simulations and winning rate prediction. The proposed robotic prediction ...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''. [[Advances in Computer Games 13]]

...ture_University OPU], for example, the number of [[Monte-Carlo Tree Search|MCTS]] simulations and winning rate prediction. The proposed robotic prediction ...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''. [[Advances in Computer Games 13]]

...s://arxiv.org/abs/1607.08100 arXiv:1607.0810] » [[Monte-Carlo Tree Search|MCTS]]

...applied to trees]]). The effect of evaluation functions on the strength of MCTS algorithms, however, has not been investigated well, especially in terms of

...ombining [[Deep Learning|Deep learning]] with [[Monte-Carlo Tree Search]] (MCTS) using pure [[Reinforcement Learning|reinforcement learning]] aka self play

...w.talkchess.com/forum3/viewtopic.php?f=7&t=71301&start=8 Re: A question to MCTS + NN experts] by [[Thomas Dybdahl Ahle]], [[CCC]], August 04, 2019

...ver]], [[ChessBase|ChessBase News]], June 15, 2018 » [[Komodo#MCTS|Komodo MCTS]]

[[Category:MCTS]]

[[Category:MCTS]]

...r [[#disqualificationKomodoMCTS|disqualification]] of [[Komodo#MCTS|Komodo MCTS]]</ref> | [[Komodo#MCTS|Komodo MCTS]]

| [[Komodo#MCTS|Komodo MCTS]] | [[Komodo#MCTS|KomodoMCTS 2301.00]]

| [[Komodo#MCTS|Komodo MCTS]] | [[Komodo#MCTS|Komodo MCTS 2381.00]]

=Exact-Win-MCTS=

...h [[Shun-Shii Lin]] et al. on improvements in [[Monte-Carlo Tree Search]] (MCTS), ...ipedia.org/wiki/Connection_game connection games]) proposing a [[Minimax]] MCTS hybrid <ref>[[Shun-Shii Lin]], [[Chih-Hung Chen]], [[Yu-Heng Chen]], [[Wei-

...ture_University OPU], for example, the number of [[Monte-Carlo Tree Search|MCTS]] simulations and winning rate prediction. The proposed robotic prediction

...ombining [[Deep Learning|Deep learning]] with [[Monte-Carlo Tree Search]] (MCTS) <ref>[[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioan [[Category:MCTS]]

* [http://www.talkchess.com/forum/viewtopic.php?t=67235 MCTS beginner questions] by [[Martin Fierz]], [[CCC]], April 25, 2018 » [[Monte * [http://www.talkchess.com/forum3/viewtopic.php?f=7&t=67302 MCTS with minmax backup operator?] by [[Martin Fierz]], [[CCC]], May 01, 2018

...based on the ideas of [[AlphaZero]], and applies [[Monte-Carlo Tree Search|MCTS]]/[[Christopher D. Rosin#PUCT|PUCT]] along with 8x128 value and policy nets

| [[Komodo#MCTS|Komodo MCTS]] | [[Komodo#MCTS|KomodoMCTS 2484.00]]

...th the advent of [[Deep Learning|deep learning]] [[Monte-Carlo Tree Search|MCTS]] chess engines after the [[AlphaZero]] publications, Warren D. Smith contr

...nd [[UCT]] <ref>[[David Tolpin]], [[Solomon Eyal Shimony]] ('''2012'''). ''MCTS Based on Simple Regret''. [[Conferences#AAAI-2012|AAAI-2012]], [https://arx * [[David Tolpin]], [[Solomon Eyal Shimony]] ('''2012'''). ''MCTS Based on Simple Regret''. [[Conferences#AAAI-2012|AAAI-2012]], [https://arx

* [http://www.talkchess.com/forum3/viewtopic.php?f=2&t=70295 SugaR MCTS Learning (New)] by supersharp77, [[CCC]], March 24, 2019

...cember 06, 2017 » [[Stockfish]], [[AlphaZero]], [[Monte-Carlo Tree Search|MCTS]]

...he research was conducted a few years before the [[Monte-Carlo Tree Search|MCTS]] revolution appeared in computer Go, not to mention the [[Deep Learning|de

...s://ieeexplore.ieee.org/document/6932868 Knowledge-based fast evolutionary MCTS for general video game playing]''. [[IEEE#CIG|IEEE CIG 2014]], [http://www.

1. Teaching other people how simple it is to write a basic mcts/nn engine with a0lite python. 3. Combining ab/nnue and mcts/nn in a hybrid approach. (Was a0lite julia, renamed Bender)

...>[https://github.com/StuartRiffle/Jaglavak GitHub - StuartRiffle/Jaglavak: MCTS chess engine for GPU and SIMD]</ref>, both targeting [[SIMD and SWAR Techni

Unlike Pigeon, Jaglavak performs a [[Monte-Carlo Tree Search|MCTS]] and uses the [[UCT]] formula to guide the selection of a node. * [https://github.com/StuartRiffle/Jaglavak GitHub - StuartRiffle/Jaglavak: MCTS chess engine for GPU and SIMD]

...]], [[CCC]], July 17, 2019 » [[Deep Learning]], [[Monte-Carlo Tree Search|MCTS]]

...w.talkchess.com/forum3/viewtopic.php?f=7&t=71301&start=8 Re: A question to MCTS + NN experts] by [[Thomas Dybdahl Ahle]], [[CCC]], August 04, 2019 [[Category:MCTS]]

...rum3/viewtopic.php?f=7&t=66886&start=1 Re: comparing minimax and averaging MCTS with alphabeta rollouts] by [[Bojun Guo]], [[CCC]], March 20, 2018 » [[Mon

..., October 23, 2016 » [[Deep Learning]], [[Go]], [[Monte-Carlo Tree Search|MCTS]] * [http://www.talkchess.com/forum3/viewtopic.php?f=2&t=68875 Komodo MCTS scales worse with TC than Komodo A/B?] by [[Kai Laskos]], [[CCC]], November

...r classical [[Alpha-Beta|alpha-beta]] as well as [[Monte-Carlo Tree Search|MCTS]]. [[Category:MCTS]]

...rlo_tree_search#Exploration_and_exploitation Exploration and exploitation (MCTS) from Wikipedia]

Ceres provides an [[Monte-Carlo Tree Search|MCTS]] implementation with many novel algorithmic improvements and low level opt * [https://github.com/dje-dev/Ceres GitHub - dje-dev/Ceres: Ceres - an MCTS chess engine for research and recreation]

Actually he works on back-porting [[Ceres|Ceres']] [[Monte-Carlo Tree Search|MCTS]] algorithmic improvements to [[Leela Chess Zero#Lc0|Lc0]], such as the par

...chapter/10.1007/978-3-642-31866-5_8 Towards a Solution of 7x7 Go with Meta-MCTS]''. [[Advances in Computer Games 13]] ...[Julien Dehos]] ('''2015'''). ''On the Tactical and Strategic Behaviour of MCTS when Biasing Random Simulations''. [[ICGA Journal#38_2|ICGA Journal, Vol. 3

...pired by the [[Deep Learning|deep learning]] and [[Monte-Carlo Tree Search|MCTS]] techniques described in [[DeepMind|DeepMind's]] [[AlphaZero]] papers ...ptionally features an improvement of AlphaZero's [[Monte-Carlo Tree Search|MCTS]] / [[Christopher D. Rosin#PUCT|PUCT]] algorithm, considering [[Transpositi

...] on an improvement of [[AlphaZero|AlphaZero's]] [[Monte-Carlo Tree Search|MCTS]] / [[Christopher D. Rosin#PUCT|PUCT]] algorithm considering [[Transpositio

...d on an improvement of [[AlphaZero|AlphaZero's]] [[Monte-Carlo Tree Search|MCTS]] / [[Christopher D. Rosin#PUCT|PUCT]] algorithm considering [[Transpositio * [[Patrick Korus]] ('''2020'''). ''An Evaluation of MCTS Methods for Continuous Control Tasks''. B.Sc. thesis, [[Darmstadt Universit

...o MCTS] by [[Mark Lefler]], [[CCC]], June 12, 2019 » [[Komodo#MCTS|Komodo MCTS]]</ref>. [[Category:MCTS]]