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https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers

A curated list of Monte Carlo tree search papers with implementations.
https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers

List: awesome-monte-carlo-tree-search-papers

atari deep-learning deep-q-learning learning machine-learning machine-learning-algorithms monte-carlo monte-carlo-tree-search policy-evaluation policy-gradient q-learning reinforcement-learning reinforcement-learning-agent reinforcement-learning-algorithms rl tree-search

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A curated list of Monte Carlo tree search papers with implementations.

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# Awesome Monte Carlo Tree Search Papers.

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-----------------------------------------



A curated list of Monte Carlo tree search papers with implementations from the following conferences/journals:



- Machine learning

   * [NeurIPS](https://nips.cc/)

   * [ICML](https://icml.cc/)

- Computer vision

   * [CVPR](http://cvpr2019.thecvf.com/)

   * [ICCV](http://iccv2019.thecvf.com/)

- Natural language processing

   * [ACL](http://www.acl2019.org/EN/index.xhtml)

- Data

   * [KDD](https://www.kdd.org/)

- Artificial intelligence

   * [AAAI](https://www.aaai.org/)

   * [AISTATS](https://www.aistats.org/)

   * [IJCAI](https://www.ijcai.org/)

   * [UAI](http://www.auai.org/)

- Robotics

   * [RAS](https://www.journals.elsevier.com/robotics-and-autonomous-systems)

- Games

   * [CIG](http://www.ieee-cig.org/)



Similar collections about [graph classification](https://github.com/benedekrozemberczki/awesome-graph-classification), [gradient boosting](https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers), [classification/regression trees](https://github.com/benedekrozemberczki/awesome-decision-tree-papers), [fraud detection](https://github.com/benedekrozemberczki/awesome-fraud-detection-papers), and [community detection](https://github.com/benedekrozemberczki/awesome-community-detection) papers with implementations.



## 2023

- **Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search (ICLR 2023)**

  - Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun

  - [[Paper]](https://arxiv.org/abs/2205.13134)



## 2022

- **Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework (AAAI 2022)**

  - Elias B. Khalil, Pashootan Vaezipoor, Bistra Dilkina

  - [[Paper]](https://arxiv.org/abs/2110.08423)



- **NSGZero: Efficiently Learning Non-exploitable Policy in Large-Scale Network Security Games with Neural Monte Carlo Tree Search (AAAI 2022)**

  - Wanqi Xue, Bo An, Chai Kiat Yeo

  - [[Paper]](https://arxiv.org/abs/2201.07224)



- **Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability Using Tree Search and Graph Neural Networks (AAAI 2022)**

  - Kevin Osanlou, Jeremy Frank, Andrei Bursuc, Tristan Cazenave, Eric Jacopin, Christophe Guettier, J. Benton

  - [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/21224)



- **Qubit Routing Using Graph Neural Network Aided Monte Carlo Tree Search (AAAI 2022)**

  - Animesh Sinha, Utkarsh Azad, Harjinder Singh

  - [[Paper]](https://arxiv.org/abs/2104.01992)



- **Split Moves for Monte-Carlo Tree Search (AAAI 2022)**

  - Jakub Kowalski, Maksymilian Mika, Wojciech Pawlik, Jakub Sutowicz, Marek Szykula, Mark H. M. Winands

  - [[Paper]](https://arxiv.org/abs/2112.07761)



- **Procrastinated Tree Search: Black-Box Optimization with Delayed%2C Noisy and Multi-Fidelity Feedback (AAAI 2022)**

  - Junxiong Wang, Debabrota Basu, Immanuel Trummer

  - [[Paper]](https://arxiv.org/abs/2110.07232)



- **Enabling Arbitrary Translation Objectives with Adaptive Tree Search (ICLR 2022)**

  - Wang Ling, Wojciech Stokowiec, Domenic Donato, Chris Dyer, Lei Yu, Laurent Sartran, Austin Matthews

  - [[Paper]](https://en.x-mol.com/paper/article/1496885785571840000)



- **What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization (ICLR 2022)**

  - Maximili1an Böther, Otto Kißig, Martin Taraz, Sarel Cohen, Karen Seidel, Tobias Friedrich

  - [[Paper]](https://arxiv.org/abs/2201.10494)



- **Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search (IJCAI 2022)**

  - Kenshi Abe, Junpei Komiyama, Atsushi Iwasaki

  - [[Paper]](https://www.ijcai.org/proceedings/2022/1)



- **Fast and Accurate User Cold-Start Learning Using Monte Carlo Tree Search (RECSYS 2022)**

  - Dilina Chandika Rajapakse, Douglas Leith

  - [[Paper]](https://www.scss.tcd.ie/Doug.Leith/pubs/recsys22-35.pdf)



## 2021



- **Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search (AAAI 2021)**

  - Li-Cheng Lan, Ti-Rong Wu, I-Chen Wu, Cho-Jui Hsieh

  - [[Paper]](https://arxiv.org/abs/2012.07910)



- **Dec-SGTS: Decentralized Sub-Goal Tree Search for Multi-Agent Coordination (AAAI 2021)**

  - Minglong Li, Zhongxuan Cai, Wenjing Yang, Lixia Wu, Yinghui Xu, Ji Wang

  - [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/17345)



- **Improved POMDP Tree Search Planning with Prioritized Action Branching (AAAI 2021)**

  - John Mern, Anil Yildiz, Lawrence Bush, Tapan Mukerji, Mykel J. Kochenderfer

  - [[Paper]](https://arxiv.org/abs/2010.03599)



- **Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search (AAAI 2021)**

  - Alvaro Velasquez, Brett Bissey, Lior Barak, Andre Beckus, Ismail Alkhouri, Daniel Melcer, George K. Atia

  - [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/17427)



- **Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model (AAAI 2021)**

  - Felix Mohr, Viktor Bengs, Eyke Hüllermeier

  - [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/17468)



- **Learning to Pack: A Data-Driven Tree Search Algorithm for Large-Scale 3D Bin Packing Problem (CIKM 2021)**

  - Qianwen Zhu, Xihan Li, Zihan Zhang, Zhixing Luo, Xialiang Tong, Mingxuan Yuan, Jia Zeng

  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3459637.3481933)



- **Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design (ICLR 2021)**

  - Xiufeng Yang, Tanuj Kr Aasawat, Kazuki Yoshizoe

  - [[Paper]](https://arxiv.org/abs/2006.10504)



- **Convex Regularization in Monte-Carlo Tree Search (ICML 2021)**

  - Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen

  - [[Paper]](https://arxiv.org/abs/2007.00391)



- **Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu (IJCAI 2021)**

  - Yunsheng Zhang, Dong Yan, Bei Shi, Haobo Fu, Qiang Fu, Hang Su, Jun Zhu, Ning Chen

  - [[Paper]](https://www.ijcai.org/proceedings/2021/470)



## 2020



- **Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds (AAAI 2020)**

  - Beomjoon Kim, Kyungjae Lee, Sungbin Lim, Leslie Pack Kaelbling, Tomás Lozano-Pérez

  - [[Paper]](https://www.aaai.org/Papers/AAAI/2020GB/AAAI-KimB.1282.pdf)



- **Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search (AAAI 2020)**

  - Linnan Wang, Yiyang Zhao, Yuu Jinnai, Yuandong Tian, Rodrigo Fonseca

  - [[Paper]](https://arxiv.org/abs/1805.07440)

  - [[Code]](https://github.com/linnanwang/AlphaX-NASBench101)



- **Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients (AAAI 2020)**

  - Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim

  - [[Paper]](https://www.ijcai.org/Proceedings/16/Papers/104.pdf)

  - [[Code]](https://github.com/leekwoon/KR-DL-UCT)

  

- **Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions (AISTATS 2020)**

  - Lars Buesing, Nicolas Heess, Theophane Weber

  - [[Paper]](https://arxiv.org/abs/1910.06862)



- **Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search (ICLR 2020)**

  - Anji Liu, Jianshu Chen, Mingze Yu, Yu Zhai, Xuewen Zhou, Ji Liu

  - [[Paper]](https://openreview.net/forum?id=BJlQtJSKDB)

  - [[Code]](https://github.com/brilee/python_uct)

  

- **Information Particle Filter Tree: An Online Algorithm for POMDPs with Belief-Based Rewards on Continuous Domains (ICML 2020)**

  - Johannes Fischer, Ömer Sahin Tas

  - [[Paper]](http://proceedings.mlr.press/v119/fischer20a.html)

  - [[Code]](https://github.com/johannes-fischer/icml2020_ipft)



- **Sub-Goal Trees a Framework for Goal-Based Reinforcement Learning (ICML 2020)**

  - Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar

  - [[Paper]](https://arxiv.org/abs/2002.12361)

  

- **Monte-Carlo Tree Search for Scalable Coalition Formation (IJCAI 2020)**

  - Feng Wu, Sarvapali D. Ramchurn

  - [[Paper]](https://www.ijcai.org/Proceedings/2020/57)



- **Generalized Mean Estimation in Monte-Carlo Tree Search (IJCAI 2020)**

  - Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

  - [[Paper]](https://arxiv.org/abs/1911.00384)



- **Sparse Tree Search Optimality Guarantees in POMDPs with Continuous Observation Spaces (IJCAI 2020)**

  - Michael H. Lim, Claire Tomlin, Zachary N. Sunberg

  - [[Paper]](https://arxiv.org/abs/1910.04332)

  

- **Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions (NeurIPS 2020)**

  - Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai

  - [[Paper]](https://arxiv.org/abs/1907.10154)



- **Extracting Knowledge from Web Text with Monte Carlo Tree Search (WWW 2020)**

  - Guiliang Liu, Xu Li, Jiakang Wang, Mingming Sun, Ping Li

  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3366423.3380010)



## 2019

- **ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search (AAAI 2019)**

  - Shangtong Zhang, Hengshuai Yao

  - [[Paper]](https://arxiv.org/abs/1811.02696)

  - [[Code]](https://github.com/ShangtongZhang/DeepRL)



- **A Monte Carlo Tree Search Player for Birds of a Feather Solitaire (AAAI 2019)**

  - Christian Roberson, Katarina Sperduto

  - [[Paper]](https://aaai.org/ojs/index.php/AAAI/article/view/5036)

  - [[Code]](http://cs.gettysburg.edu/~tneller/puzzles/boaf/)



- **Vine Copula Structure Learning via Monte Carlo Tree Search (AISTATS 2019)**

  - Bo Chang, Shenyi Pan, Harry Joe

  - [[Paper]](http://proceedings.mlr.press/v89/chang19a/chang19a.pdf)

  - [[Code]](https://github.com/changebo/Vine_MCTS)



- **Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach (AISTATS 2019)**

  - Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai

  - [[Paper]](https://arxiv.org/abs/1810.10482)

  - [[Code]](https://github.com/rajatsen91/MFTREE_DET)



- **Reinforcement Learning Based Monte Carlo Tree Search for Temporal Path Discovery (ICDM 2019)**

  - Pengfei Ding, Guanfeng Liu, Pengpeng Zhao, An Liu, Zhixu Li, Kai Zheng

  - [[Paper]](https://zheng-kai.com/paper/icdm_2019_b.pdf)



- **Monte Carlo Tree Search for Policy Optimization (IJCAI 2019)**

  - Xiaobai Ma, Katherine Rose Driggs-Campbell, Zongzhang Zhang, Mykel J. Kochenderfer

  - [[Paper]](https://www.ijcai.org/proceedings/2019/0432.pdf)



- **Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search (IJCAI 2019)**

  - Thomas Gabor, Jan Peter, Thomy Phan, Christian Meyer, Claudia Linnhoff-Popien

  - [[Paper]](https://www.ijcai.org/proceedings/2019/0772.pdf)

  - [[Code]](https://github.com/jnptr/subgoal-mcts)



- **Automated Machine Learning with Monte-Carlo Tree Search (IJCAI 2019)**

  - Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag

  - [[Paper]](https://www.ijcai.org/proceedings/2019/0457.pdf)

  - [[Code]](https://github.com/herilalaina/mosaic_ml)



- **Multiple Policy Value Monte Carlo Tree Search (IJCAI 2019)**

  - Li-Cheng Lan, Wei Li, Ting-Han Wei, I-Chen Wu

  - [[Paper]](https://www.ijcai.org/proceedings/2019/0653.pdf)



- **Learning Compositional Neural Programs with Recursive Tree Search and Planning (NeurIPS 2019)**

  - Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas

  - [[Paper]](https://arxiv.org/abs/1905.12941)



## 2018

- **Monte Carlo Methods for the Game Kingdomino (CIG 2018)**

  - Magnus Gedda, Mikael Z. Lagerkvist, Martin Butler

  - [[Paper]](https://arxiv.org/abs/1807.04458)

  - [[Code]](https://github.com/mgedda/kdom-ai)

  - [[Game Server]](https://github.com/mratin/kdom)



- **Reset-free Trial-and-Error Learning for Robot Damage Recovery (RAS 2018)**

  - Konstantinos Chatzilygeroudis, Vassilis Vassiliades, Jean-Baptiste Mouret

  - [[Paper]](https://arxiv.org/pdf/1610.04213.pdf)

  - [[Code]](https://github.com/resibots/chatzilygeroudis_2018_rte)

  - [[MCTS C++ Library]](https://github.com/resibots/mcts)



- **Memory-Augmented Monte Carlo Tree Search (AAAI 2018)**

  - Chenjun Xiao, Jincheng Mei, Martin Müller

  - [[Paper]](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17139)



- **Feedback-Based Tree Search for Reinforcement Learning (ICML 2018)**

  - Daniel R. Jiang, Emmanuel Ekwedike, Han Liu

  - [[Paper]](https://arxiv.org/abs/1805.05935)



- **Extended Increasing Cost Tree Search for Non-Unit Cost Domains (IJCAI 2018)**

  - Thayne T. Walker, Nathan R. Sturtevant, Ariel Felner

  - [[Paper]](https://www.ijcai.org/proceedings/2018/74)



- **Three-Head Neural Network Architecture for Monte Carlo Tree Search (IJCAI 2018)**

  - Chao Gao, Martin Müller, Ryan Hayward

  - [[Paper]](https://www.ijcai.org/proceedings/2018/523)



- **Bidding in Periodic Double Auctions Using Heuristics and Dynamic Monte Carlo Tree Search (IJCAI 2018)**

  - Moinul Morshed Porag Chowdhury, Christopher Kiekintveld, Son Tran, William Yeoh

  - [[Paper]](https://www.ijcai.org/proceedings/2018/23)



- **Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search (NIPS 2018)**

  - Zhuwen Li, Qifeng Chen, Vladlen Koltun

  - [[Paper]](https://arxiv.org/abs/1810.10659)



- **M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search (NIPS 2018)**

  - Yelong Shen, Jianshu Chen, Po-Sen Huang, Yuqing Guo, Jianfeng Gao

  - [[Paper]](https://arxiv.org/abs/1802.04394)



- **Single-Agent Policy Tree Search With Guarantees (NIPS 2018)**

  - Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber

  - [[Paper]](https://arxiv.org/abs/1811.10928)



- **Monte-Carlo Tree Search for Constrained POMDPs (NIPS 2018)**

  - Jongmin Lee, Geon-hyeong Kim, Pascal Poupart, Kee-Eung Kim

  - [[Paper]](https://cs.uwaterloo.ca/~ppoupart/publications/constrained-pomdps/mcts-constrained-pomdps-paper.pdf)



## 2017

- **An Analysis of Monte Carlo Tree Search (AAAI 2017)**

  - Steven James, George Dimitri Konidaris, Benjamin Rosman

  - [[Paper]](https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14886)



- **Beyond Monte Carlo Tree Search: Playing Go with Deep Alternative Neural Network and Long-Term Evaluation (AAAI 2017)**

  - Jinzhuo Wang, Wenmin Wang, Ronggang Wang, Wen Gao

  - [[Paper]](https://arxiv.org/abs/1706.04052)



- **Designing Better Playlists with Monte Carlo Tree Search (AAAI 2017)**

  - Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, Peter Stone

  - [[Paper]](https://www.cs.utexas.edu/~pstone/Papers/bib2html-links/IAAI2017-eladlieb.pdf)



- **Learning in POMDPs with Monte Carlo Tree Search (ICML 2017)**

  - Sammie Katt, Frans A. Oliehoek, Christopher Amato

  - [[Paper]](https://arxiv.org/abs/1806.05631)



- **Learning to Run Heuristics in Tree Search (IJCAI 2017)**

  - Elias B. Khalil, Bistra Dilkina, George L. Nemhauser, Shabbir Ahmed, Yufen Shao

  - [[Paper]](https://www.ijcai.org/proceedings/2017/92)



- **Estimating the Size of Search Trees by Sampling with Domain Knowledge (IJCAI 2017)**

  - Gleb Belov, Samuel Esler, Dylan Fernando, Pierre Le Bodic, George L. Nemhauser

  - [[Paper]](https://www.ijcai.org/proceedings/2017/67)



- **A Monte Carlo Tree Search Approach to Active Malware Analysis (IJCAI 2017)**

  - Riccardo Sartea, Alessandro Farinelli

  - [[Paper]](https://www.ijcai.org/proceedings/2017/535)



- **Monte-Carlo Tree Search by Best Arm Identification (NIPS 2017)**

  - Emilie Kaufmann, Wouter M. Koolen

  - [[Paper]](https://arxiv.org/abs/1706.02986)



- **Thinking Fast and Slow with Deep Learning and Tree Search (NIPS 2017)**

  - Thomas Anthony, Zheng Tian, David Barber

  - [[Paper]](https://arxiv.org/abs/1705.08439)



- **Monte-Carlo Tree Search using Batch Value of Perfect Information (UAI 2017)**

  - Shahaf S. Shperberg, Solomon Eyal Shimony, Ariel Felner

  - [[Paper]](http://auai.org/uai2017/proceedings/papers/37.pdf)



## 2016

- **Using Domain Knowledge to Improve Monte-Carlo Tree Search Performance in Parameterized Poker Squares (AAAI 2016)**

  - Robert Arrington, Clay Langley, Steven Bogaerts

  - [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/11809)



- **Monte Carlo Tree Search for Multi-Robot Task Allocation (AAAI 2016)**

  - Bilal Kartal, Ernesto Nunes, Julio Godoy, Maria L. Gini

  - [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12154)



- **Large Scale Hard Sample Mining with Monte Carlo Tree Search (CVPR 2016)**

  - Olivier Canévet, François Fleuret

  - [[Paper]](https://www.idiap.ch/~fleuret/papers/canevet-fleuret-cvpr2016.pdf)



- **On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search (ICML 2016)**

  - Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone

  - [[Paper]](https://www.cs.utexas.edu/~eladlieb/ICML2016.pdf)



- **Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games (IJCAI 2016)**

  - Xiaoxiao Guo, Satinder P. Singh, Richard L. Lewis, Honglak Lee

  - [[Paper]](https://arxiv.org/abs/1604.07095)



- **Monte Carlo Tree Search in Continuous Action Spaces with Execution Uncertainty (IJCAI 2016)**

  - Timothy Yee, Viliam Lisý, Michael H. Bowling

  - [[Paper]](https://www.ijcai.org/Proceedings/16/Papers/104.pdf)



- **Learning Predictive State Representations via Monte-Carlo Tree Search (IJCAI 2016)**

  - Yunlong Liu, Hexing Zhu, Yifeng Zeng, Zongxiong Dai

  - [[Paper]](https://pdfs.semanticscholar.org/8056/df11094fc96d76826403f8b339dc14aa821f.pdf)



## 2015

- **Efficient Globally Optimal Consensus Maximisation with Tree Search (CVPR 2015)**

  - Tat-Jun Chin, Pulak Purkait, Anders P. Eriksson, David Suter

  - [[Paper]](https://zpascal.net/cvpr2015/Chin_Efficient_Globally_Optimal_2015_CVPR_paper.pdf)



- **Interplanetary Trajectory Planning with Monte Carlo Tree Search (IJCAI 2015)**

  - Daniel Hennes, Dario Izzo

  - [[Paper]](https://pdfs.semanticscholar.org/ce42/53ca1c5b16e96cdbefae75649cd2588f42f3.pdf)



## 2014

- **State Aggregation in Monte Carlo Tree Search (AAAI 2014)**

  - Jesse Hostetler, Alan Fern, Tom Dietterich

  - [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI14/paper/download/8439/8712)



- **Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning (NIPS 2014)**

  - Xiaoxiao Guo, Satinder P. Singh, Honglak Lee, Richard L. Lewis, Xiaoshi Wang

  - [[Paper]](https://web.eecs.umich.edu/~baveja/Papers/UCTtoCNNsAtariGames-FinalVersion.pdf)



- **Learning Partial Policies to Speedup MDP Tree Search (UAI 2014)**

  - Jervis Pinto, Alan Fern

  - [[Paper]](http://www.jmlr.org/papers/volume18/15-251/15-251.pdf)



## 2013

- **Monte Carlo Tree Search for Scheduling Activity Recognition (ICCV 2013)**

  - Mohamed R. Amer, Sinisa Todorovic, Alan Fern, Song-Chun Zhu

  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.405.5916&rep=rep1&type=pdf)



- **Convergence of Monte Carlo Tree Search in Simultaneous Move Games (NIPS 2013)**

  - Viliam Lisý, Vojtech Kovarík, Marc Lanctot, Branislav Bosanský

  - [[Paper]](https://papers.nips.cc/paper/5145-convergence-of-monte-carlo-tree-search-in-simultaneous-move-games)



- **Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree Search (NIPS 2013)**

  - Aijun Bai, Feng Wu, Xiaoping Chen

  - [[Paper]](https://papers.nips.cc/paper/5111-bayesian-mixture-modelling-and-inference-based-thompson-sampling-in-monte-carlo-tree-search)



## 2012

- **Generalized Monte-Carlo Tree Search Extensions for General Game Playing (AAAI 2012)**

  - Hilmar Finnsson

  - [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI12/paper/viewFile/4935/5300)



## 2011

- **A Local Monte Carlo Tree Search Approach in Deterministic Planning (AAAI 2011)**

  - Fan Xie, Hootan Nakhost, Martin Müller

  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.699.3833&rep=rep1&type=pdf)



- **Real-Time Solving of Quantified CSPs Based on Monte-Carlo Game Tree Search (IJCAI 2011)**

  - Satomi Baba, Yongjoon Joe, Atsushi Iwasaki, Makoto Yokoo

  - [[Paper]](https://www.ijcai.org/Proceedings/11/Papers/116.pdf)



- **Nested Rollout Policy Adaptation for Monte Carlo Tree Search (IJCAI 2011)**

  - Christopher D. Rosin

  - [[Paper]](https://www.ijcai.org/Proceedings/11/Papers/115.pdf)



- **Variance Reduction in Monte-Carlo Tree Search (NIPS 2011)**

  - Joel Veness, Marc Lanctot, Michael H. Bowling

  - [[Paper]](https://papers.nips.cc/paper/4288-variance-reduction-in-monte-carlo-tree-search)



- **Learning Is Planning: Near Bayes-Optimal Reinforcement Learning via Monte-Carlo Tree Search (UAI 2011)**

  - John Asmuth, Michael L. Littman

  - [[Paper]](https://arxiv.org/abs/1202.3699)



## 2010

- **Understanding the Success of Perfect Information Monte Carlo Sampling in Game Tree Search (AAAI 2010)**

  - Jeffrey Richard Long, Nathan R. Sturtevant, Michael Buro, Timothy Furtak

  - [[Paper]](https://pdfs.semanticscholar.org/011e/2c79575721764c127e210c9d8105a6305e70.pdf)



- **Bayesian Inference in Monte-Carlo Tree Search (UAI 2010)**

  - Gerald Tesauro, V. T. Rajan, Richard Segal

  - [[Paper]](https://arxiv.org/abs/1203.3519)



## 2009

- **Monte Carlo Tree Search Techniques in the Game of Kriegspiel (IJCAI 2009)**

  - Paolo Ciancarini, Gian Piero Favini

  - [[Paper]](https://www.aaai.org/ocs/index.php/IJCAI/IJCAI-09/paper/viewFile/396/693)



- **Bootstrapping from Game Tree Search (NIPS 2009)**

  - Joel Veness, David Silver, William T. B. Uther, Alan Blair

  - [[Paper]](https://papers.nips.cc/paper/3722-bootstrapping-from-game-tree-search)



## 2008

- **Direct Mining of Discriminative and Essential Frequent Patterns via Model-Based Search Tree (KDD 2008)**

  - Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Yan, Jiawei Han, Philip S. Yu, Olivier Verscheure

  - [[Paper]](http://www1.se.cuhk.edu.hk/~hcheng/paper/kdd08mbt.pdf)



## 2007

- **Bandit Algorithms for Tree Search (UAI 2007)**

  - Pierre-Arnaud Coquelin, Rémi Munos

  - [[Paper]](https://arxiv.org/pdf/1408.2028.pdf)



## 2006

- **Properties of Forward Pruning in Game-Tree Search (AAAI 2006)**

  - Yew Jin Lim, Wee Sun Lee

  - [[Paper]](https://dl.acm.org/citation.cfm?id=1597351)



- **Graph Branch Algorithm: An Optimum Tree Search Method for Scored Dependency Graph with Arc Co-Occurrence Constraints (ACL 2006)**

  - Hideki Hirakawa

  - [[Paper]](https://www.aclweb.org/anthology/P06-2047/)



## 2005

- **Game-Tree Search with Combinatorially Large Belief States (IJCAI 2005)**

  - Austin Parker, Dana S. Nau, V. S. Subrahmanian

  - [[Paper]](https://www.ijcai.org/Proceedings/05/Papers/0878.pdf)



## 2003

- **Solving Finite Domain Constraint Hierarchies by Local Consistency and Tree Search (IJCAI 2003)**

  - Stefano Bistarelli, Philippe Codognet, Kin Chuen Hui, Jimmy Ho-Man Lee

  - [[Paper]](https://www.ijcai.org/Proceedings/03/Papers/200.pdf)



## 2001

- **Incomplete Tree Search using Adaptive Probing (IJCAI 2001)**

  - Wheeler Ruml

  - [[Paper]](https://dash.harvard.edu/bitstream/handle/1/23017275/tr-02-01.pdf?sequence%3D1)



## 1998

- **KnightCap: A Chess Programm That Learns by Combining TD with Game-Tree Search (ICML 1998)**

  - Jonathan Baxter, Andrew Tridgell, Lex Weaver

  - [[Paper]](https://arxiv.org/abs/cs/9901002)



## 1988

- **A Tree Search Algorithm for Target Detection in Image Sequences (CVPR 1988)**

  - Steven D. Blostein, Thomas S. Huang

  - [[Paper]](https://ieeexplore.ieee.org/document/196309)



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**License**



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