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The use of [[Sequential Monte Carlo method|Sequential Monte Carlo]] in advanced [[signal processing]] and [[Bayesian inference]] is more recent. It was in 1993, that Gordon et al., published in their seminal work<ref>{{cite journal|title=Novel approach to nonlinear/non-Gaussian Bayesian state estimation |journal=IEE Proceedings F - Radar and Signal Processing |date=April 1993 |issn=0956-375X |pages=107–113 |volume=140 |issue=2 |author-first1=N.J. |author-last1=Gordon |author-first2=D.J. |author-last2=Salmond |author-first3 = A.F.M. |author-last3=Smith |doi=10.1049/ip-f-2.1993.0015 |s2cid=12644877 }}</ref> the first application of a Monte Carlo [[Resampling (statistics)|resampling]] algorithm in Bayesian statistical inference. The authors named their algorithm 'the bootstrap filter', and demonstrated that compared to other filtering methods, their bootstrap algorithm does not require any assumption about that state-space or the noise of the system. We also quote another pioneering article in this field of Genshiro Kitagawa on a related "Monte Carlo filter",<ref>{{cite journal
|author-last=Kitagawa |author-first=G. |year=1996 |title=Monte carlo filter and smoother for non-Gaussian nonlinear state space models |volume=5 |issue=1 |journal=Journal of Computational and Graphical Statistics |pages=1–25 |doi=10.2307/1390750 |jstor=1390750}}</ref> and the ones by Pierre Del Moral<ref name="dm9622">{{cite journal |author-last1=Del Moral |author-first1=Pierre |title=Non Linear Filtering: Interacting Particle Solution. |journal=Markov Processes and Related Fields |date=1996 |volume=2 |issue=4 |pages=555–580 |url=http://web.maths.unsw.edu.au/~peterdel-moral/mprfs.pdf |access-date=2015-06-11 |archive-date=2016-03-04 |archive-url=https://web.archive.org/web/20160304052857/http://web.maths.unsw.edu.au/~peterdel-moral/mprfs.pdf |url-status=dead }}</ref> and Himilcon Carvalho, Pierre Del Moral, André Monin and Gérard Salut<ref>{{cite journal |author-last1=Carvalho |author-first1=Himilcon |author-last2=Del Moral |author-first2=Pierre |author-last3=Monin |author-first3=André |author-last4=Salut |author-first4=Gérard |title=Optimal Non-linear Filtering in GPS/INS Integration. |journal=IEEE Transactions on Aerospace and Electronic Systems |date=July 1997 |volume=33 |issue=3 |pages=835–850 |url=http://homepages.laas.fr/monin/Version_anglaise/Publications_files/GPS.pdf |bibcode=1997ITAES..33..835C |doi=10.1109/7.599254 |s2cid=27966240 |access-date=2015-06-11 |archive-date=2022-11-10 |archive-url=https://web.archive.org/web/20221110053359/https://homepages.laas.fr/monin/Version_anglaise/Publications_files/GPS.pdf |url-status=dead }}</ref> on particle filters published in the mid-1990s. Particle filters were also developed in signal processing in 1989–1992 by P. Del Moral, J. C. Noyer, G. Rigal, and G. Salut in the LAAS-CNRS in a series of restricted and classified research reports with STCAN (Service Technique des Constructions et Armes Navales), the IT company DIGILOG, and the [https://www.laas.fr/public/en LAAS-CNRS] (the Laboratory for Analysis and Architecture of Systems) on radar/sonar and GPS signal processing problems.<ref>P. Del Moral, G. Rigal, and G. Salut. "Estimation and nonlinear optimal control: An unified framework for particle solutions". LAAS-CNRS, Toulouse, Research Report no. 91137, DRET-DIGILOG- LAAS/CNRS contract, April (1991).</ref><ref>P. Del Moral, G. Rigal, and G. Salut. "Nonlinear and non Gaussian particle filters applied to inertial platform repositioning." LAAS-CNRS, Toulouse, Research Report no. 92207, STCAN/DIGILOG-LAAS/CNRS Convention STCAN no. A.91.77.013, (94p.) September (1991).</ref><ref>P. Del Moral, G. Rigal, and G. Salut. "Estimation and nonlinear optimal control: Particle resolution in filtering and estimation: Experimental results". Convention DRET no. 89.34.553.00.470.75.01, Research report no.2 (54p.), January (1992).</ref><ref>P. Del Moral, G. Rigal, and G. Salut. "Estimation and nonlinear optimal control: Particle resolution in filtering and estimation: Theoretical results".
Convention DRET no. 89.34.553.00.470.75.01, Research report no.3 (123p.), October (1992).</ref><ref>P. Del Moral, J.-Ch. Noyer, G. Rigal, and G. Salut. "Particle filters in radar signal processing: detection, estimation and air targets recognition". LAAS-CNRS, Toulouse, Research report no. 92495, December (1992).</ref><ref>P. Del Moral, G. Rigal, and G. Salut. "Estimation and nonlinear optimal control: Particle resolution in filtering and estimation". Studies on: Filtering, optimal control, and maximum likelihood estimation. Convention DRET no. 89.34.553.00.470.75.01. Research report no.4 (210p.), January (1993).</ref> These Sequential Monte Carlo methodologies can be interpreted as an acceptance-rejection sampler equipped with an interacting recycling mechanism.
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The net effect, over the course of many simulated games, is that the value of a node representing a move will go up or down, hopefully corresponding to whether or not that node represents a good move.
Monte Carlo Tree Search has been used successfully to play games such as [[Go (game)|Go]],<ref>{{cite book|chapter=Parallel Monte-Carlo Tree Search |doi=10.1007/978-3-540-87608-3_6 |volume=5131 |pages=60–71 |series=Lecture Notes in Computer Science |year=2008 |author-last1=Chaslot |author-first1=Guillaume M. J. -B |author-last2=Winands |author-first2=Mark H. M. |author-last3=Van Den Herik |author-first3=H. Jaap |title=Computers and Games |isbn=978-3-540-87607-6 |citeseerx=10.1.1.159.4373}}</ref> [[Tantrix]],<ref>{{cite report|url=https://www.tantrix.com/Tantrix/TRobot/MCTS%20Final%20Report.pdf |title=Monte-Carlo Tree Search in the game of Tantrix: Cosc490 Final Report |author-last=Bruns |author-first=Pete}}</ref> [[Battleship (game)|Battleship]],<ref>{{cite web |url=http://www0.cs.ucl.ac.uk/staff/D.Silver/web/Publications_files/pomcp.pdf |title=Monte-Carlo Planning in Large POMDPs |author-first1=David |author-last1=Silver |author-first2=Joel |author-last2=Veness |website=0.cs.ucl.ac.uk |access-date=28 October 2017 |archive-date=18 July 2016 |archive-url=https://web.archive.org/web/20160718050040/http://www0.cs.ucl.ac.uk/staff/d.silver/web/Publications_files/pomcp.pdf |url-status=dead }}</ref> [[Havannah (board game)|Havannah]],<ref>{{cite book|chapter=Improving Monte–Carlo Tree Search in Havannah |doi=10.1007/978-3-642-17928-0_10 |volume=6515 |pages=105–115|bibcode=2011LNCS.6515..105L |series=Lecture Notes in Computer Science |year=2011 |author-last1=Lorentz |author-first1=Richard J. |title=Computers and Games |isbn=978-3-642-17927-3}}</ref> and [[Arimaa]].<ref>{{cite web|url=http://www.arimaa.com/arimaa/papers/ThomasJakl/bc-thesis.pdf |author-first=Tomas |author-last=Jakl |title=Arimaa challenge – comparison study of MCTS versus alpha-beta methods |website=Arimaa.com |access-date=28 October 2017}}</ref>
{{See also|Computer Go}}
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=== Sources ===
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