40 KiB
40 KiB
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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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
- CC0 Universal (https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers/blob/master/LICENSE)
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