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* [[Thomas J. Walsh]], [[Sergiu Goschin]], [[Michael L. Littman]] ('''2010'''). ''Integrating sample-based planning and model-based reinforcement learning.'' [[AAAI]], [https://pdfs.semanticscholar.org/bdc9/bfb6ecc6fb5afb684df03d7220c46ebdbf4e.pdf pdf] » [[UCT]], [[Reinforcement Learning]]
'''2011'''
* [[Christopher D. Rosin]] ('''2011'''). ''[https://link.springer.com/article/10.1007/s10472-011-9258-6 Multi-armed bandits with episode context]''. Annals of Mathematics and Artificial Intelligence, Vol. 61, No. 3, [http://gauss.ececs.uc.edu/Workshops/isaim2010/papers/rosin.pdf ISAIM 2010 pdf]
* [[Shih-Chieh Huang]], [[Rémi Coulom]], [[Shun-Shii Lin]] ('''2011'''). ''Time Management for Monte-Carlo Tree Search Applied to the Game of Go''. TAAI 2010, [http://remi.coulom.free.fr/Publications/TimeManagement.pdf pdf]
* [[Arpad Rimmel]], [[Fabien Teytaud]], [[Tristan Cazenave]] ('''2011'''). ''Optimization of the Nested Monte-Carlo Algorithm on the Traveling Salesman Problem with Time Windows''. Evostar 2011, [http://www.lamsade.dauphine.fr/~cazenave/papers/tsptw.pdf pdf]
* [[Joel Veness]], [[Marc Lanctot]], [[Michael Bowling]] ('''2011'''). ''Variance Reduction in Monte-Carlo Tree Search''. [http://papers.nips.cc/book/advances-in-neural-information-processing-systems-24-2011 NIPS], [http://papers.nips.cc/paper/4288-variance-reduction-in-monte-carlo-tree-search.pdf pdf]
* [[Joel Veness]], [[Kee Siong Ng]], [[Marcus Hutter]], [[William Uther]] , [[David Silver]] ('''2011'''). ''A Monte-Carlo AIXI Approximation''. [https://en.wikipedia.org/wiki/Journal_of_Artificial_Intelligence_Research JAIR], Vol. 40, [http://www.aaai.org/Papers/JAIR/Vol40/JAIR-4004.pdf pdf]
* [[Christopher D. Rosin]] ('''2011'''). '' Nested Rollout Policy Adaptation for Monte Carlo Tree Search''. [[Conferences#IJCAI2011|IJCAI 2011]], [http://www.chrisrosin.com/rosin-ijcai11.pdf pdf]
'''2012'''
* [[Michael L. Littman]] ('''2012'''). ''Technical Perspective: A New Way to Search Game Trees''. [[ACM#Communications|Communications of the ACM]], Vol. 55, No. 3
