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
  • ICML
• Computer vision
  • CVPR
  • ICCV
• Natural language processing
  • ACL
• Data
  • KDD
• Artificial intelligence
  • AAAI
  • AISTATS
  • IJCAI
  • UAI
• Robotics
  • RAS
• Games
  • CIG

Similar collections about graph classification, gradient boosting, classification/regression trees, fraud detection, and community detection papers with implementations.

2025

• LiteSearch: Efficient Tree Search with Dynamic Exploration Budget for Math Reasoning (AAAI 2025)

  • Ante Wang, Linfeng Song, Ye Tian, Baolin Peng, Dian Yu, Haitao Mi, Jinsong Su, Dong Yu
  • [Paper]
  • [Code]

• Threshold UCT: Cost-Constrained Monte Carlo Tree Search with Pareto Curves (AAAI 2025)

  • Martin Kurecka, Václav Nevyhostený, Petr Novotný, Vít Uncovsk
  • [Paper]
  • [Code]

• HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree Search (AISTATS 2025)

  • Tuan Nguyen, Jay Barrett, Kwang-Sung Jun
  • [Paper]
  • [Code]

• Monte Carlo Tree Search for Graph Reasoning in Large Language Model Agents (CIKM 2025)

  • Lihui Liu
  • [Paper]
  • [Code]

• ThoughtForest-KGQA: A Multi-Chain Tree Search for Knowledge Graph Reasoning (CIKM 2025)

  • Xingrun Quan, Yongkang Zhou, Junjie Yao
  • [Paper]
  • [Code]

• Global-Local Tree Search in VLMs for 3D Indoor Scene Generation (CVPR 2025)

  • Wei Deng, Mengshi Qi, Huadong Ma
  • [Paper]
  • [Code]

• Collaborative Tree Search for Enhancing Embodied Multi-Agent Collaboration (CVPR 2025)

  • Lizheng Zu, Lin Lin, Song Fu, Na Zhao, Pan Zhou
  • [Paper]
  • [Code]

• SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement (ICLR 2025)

  • Antonis Antoniades, Albert Örwall, Kexun Zhang, Yuxi Xie, Anirudh Goyal, William Yang Wang
  • [Paper]
  • [Code]

• Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search (ICLR 2025)

  • Jonathan Light, Min Cai, Weiqin Chen, Guanzhi Wang, Xiusi Chen, Wei Cheng, Yisong Yue, Ziniu Hu
  • [Paper]
  • [Code]

• CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search (ICLR 2025)

  • Xiao-Wen Yang, Zhi Zhou, Haiming Wang, Aoxue Li, Wen-Da Wei, Hui Jin, Zhenguo Li, Yu-Feng Li
  • [Paper]
  • [Code]

• DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search (ICLR 2025)

  • Huajian Xin, Z. Z. Ren, Junxiao Song, Zhihong Shao, Wanjia Zhao, Haocheng Wang, Bo Liu, Liyue Zhang, Xuan Lu, Qiushi Du, Wenjun Gao, Haowei Zhang, Qihao Zhu, Dejian Yang, Zhibin Gou, Z. F. Wu, Fuli Luo, Chong Ruan
  • [Paper]
  • [Code]

• Epistemic Monte Carlo Tree Search (ICLR 2025)

  • Yaniv Oren, Viliam Vadocz, Matthijs T. J. Spaan, Wendelin Boehmer
  • [Paper]
  • [Code]

• Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport (ICML 2025)

  • Tuan Dam, Pascal Stenger, Lukas Schneider, Joni Pajarinen, Carlo D'Eramo, Odalric-Ambrym Maillard
  • [Paper]
  • [Code]

• Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger (ICML 2025)

  • Qi Yang, Chenghao Zhang, Lubin Fan, Kun Ding, Jieping Ye, Shiming Xiang
  • [Paper]
  • [Code]

• CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation (ICML 2025)

  • Thibaud Southiratn, Bonil Koo, Yijingxiu Lu, Sun Kim
  • [Paper]
  • [Code]

• Power Mean Estimation in Stochastic Continuous Monte-Carlo Tree Search (ICML 2025)

  • Tuan Dam
  • [Paper]
  • [Code]

• Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search (ICML 2025)

  • Boyan Li, Jiayi Zhang, Ju Fan, Yanwei Xu, Chong Chen, Nan Tang, Yuyu Luo
  • [Paper]
  • [Code]

• Policy Guided Tree Search for Enhanced LLM Reasoning (ICML 2025)

  • Yang Li
  • [Paper]
  • [Code]

• KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search (ICML 2025)

  • Haoran Luo, Haihong E, Yikai Guo, Qika Lin, Xiaobao Wu, Xinyu Mu, Wenhao Liu, Meina Song, Yifan Zhu, Anh Tuan Luu
  • [Paper]
  • [Code]

• Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design (ICML 2025)

  • Zhi Zheng, Zhuoliang Xie, Zhenkun Wang, Bryan Hooi
  • [Paper]
  • [Code]

• Language Models as Implicit Tree Search (ICML 2025)

  • Ziliang Chen, Zhao-Rong Lai, Yufeng Yang, Liangda Fang, Zhanfu Yang, Liang Lin
  • [Paper]
  • [Code]

• SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation (IJCAI 2025)

  • Bin Xu, Yiguan Lin, Yinghao Li, Yang Gao
  • [Paper]
  • [Code]

2024

• Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization (AAAI 2024)

  • Jiahao Qiu, Hui Yuan, Jinghong Zhang, Wentao Chen, Huazheng Wang, Mengdi Wang
  • [Paper]
  • [Code]

• Decentralized Monte Carlo Tree Search for Partially Observable Multi-Agent Pathfinding (AAAI 2024)

  • Alexey Skrynnik, Anton Andreychuk, Konstantin S. Yakovlev, Aleksandr Panov
  • [Paper]
  • [Code]

• Monte Carlo Tree Search in the Presence of Transition Uncertainty (AAAI 2024)

  • Farnaz Kohankhaki, Kiarash Aghakasiri, Hongming Zhang, Ting-Han Wei, Chao Gao, Martin Müller
  • [Paper]
  • [Code]

• Temporal Logic Explanations for Dynamic Decision Systems Using Anchors and Monte Carlo Tree Search %28Abstract Reprint%29 (AAAI 2024)

  • Tzu-Yi Chiu, Jerome Le Ny, Jean-Pierre David
  • [Paper]
  • [Code]

• Tree Search-Based Policy Optimization under Stochastic Execution Delay (ICLR 2024)

  • David Valensi, Esther Derman, Shie Mannor, Gal Dalal
  • [Paper]
  • [Code]

• Reinforcement Learning within Tree Search for Fast Macro Placement (ICML 2024)

  • Zijie Geng, Jie Wang, Ziyan Liu, Siyuan Xu, Zhentao Tang, Mingxuan Yuan, Jianye Hao, Yongdong Zhang, Feng Wu
  • [Paper]
  • [Code]

• Provably Efficient Long-Horizon Exploration in Monte Carlo Tree Search through State Occupancy Regularization (ICML 2024)

  • Liam Schramm, Abdeslam Boularias
  • [Paper]
  • [Code]

• Language Agent Tree Search Unifies Reasoning%2C Acting%2C and Planning in Language Models (ICML 2024)

  • Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang
  • [Paper]
  • [Code]

• Layered and Staged Monte Carlo Tree Search for SMT Strategy Synthesis (IJCAI 2024)

  • Zhengyang Lu, Stefan Siemer, Piyush Jha, Joel D. Day, Florin Manea, Vijay Ganesh
  • [Paper]
  • [Code]

• Monte Carlo Tree Search based Space Transfer for Black Box Optimization (NIPS 2024)

  • Shukuan Wang, Ke Xue, Song Lei, Xiaobin Huang, Chao Qian
  • [Paper]
  • [Code]

• Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search (NIPS 2024)

  • Nicola Dainese, Matteo Merler, Minttu Alakuijala, Pekka Marttinen
  • [Paper]
  • [Code]

• ReST-MCTS%2A: LLM Self-Training via Process Reward Guided Tree Search (NIPS 2024)

  • Dan Zhang, Sining Zhoubian, Ziniu Hu, Yisong Yue, Yuxiao Dong, Jie Tang
  • [Paper]
  • [Code]

• Speculative Monte-Carlo Tree Search (NIPS 2024)

  • Scott Cheng, Mahmut T. Kandemir, Ding-Yong Hong
  • [Paper]
  • [Code]

• Power Mean Estimation in Stochastic Monte-Carlo Tree Search (UAI 2024)

  • Tuan Dam, Odalric-Ambrym Maillard, Emilie Kaufmann
  • [Paper]
  • [Code]

• Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction (UAI 2024)

  • Yunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang
  • [Paper]
  • [Code]

• Hybrid CtrlFormer: Learning Adaptive Search Space Partition for Hybrid Action Control via Transformer-based Monte Carlo Tree Search (UAI 2024)

  • Jiashun Liu, Xiaotian Hao, Jianye Hao, Yan Zheng, Yujing Hu, Changjie Fan, Tangjie Lv, Zhipeng Hu
  • [Paper]
  • [Code]

2023

• AlphaRoute: Large-Scale Coordinated Route Planning via Monte Carlo Tree Search (AAAI 2023)

  • Guiyang Luo, Yantao Wang, Hui Zhang, Quan Yuan, Jinglin Li
  • [Paper]
  • [Code]

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

  • Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun
  • [Paper]
  • [Code]

• NuTrea: Neural Tree Search for Context-guided Multi-hop KGQA (NIPS 2023)

  • Hyeong Kyu Choi, Seunghun Lee, Jaewon Chu, Hyunwoo J. Kim
  • [Paper]
  • [Code]

• LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (NIPS 2023)

  • Yazhe Niu, Yuan Pu, Zhenjie Yang, Xueyan Li, Tong Zhou, Jiyuan Ren, Shuai Hu, Hongsheng Li, Yu Liu
  • [Paper]
  • [Code]

• Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction (NIPS 2023)

  • Yangqing Fu, Ming Sun, Buqing Nie, Yue Gao
  • [Paper]
  • [Code]

• Monte Carlo Tree Search with Boltzmann Exploration (NIPS 2023)

  • Michael Painter, Mohamed Baioumy, Nick Hawes, Bruno Lacerda
  • [Paper]
  • [Code]

2022

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

  • Elias B. Khalil, Pashootan Vaezipoor, Bistra Dilkina
  • [Paper]

• 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]

• 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]

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

  • Animesh Sinha, Utkarsh Azad, Harjinder Singh
  • [Paper]

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

  • Jakub Kowalski, Maksymilian Mika, Wojciech Pawlik, Jakub Sutowicz, Marek Szykula, Mark H. M. Winands
  • [Paper]

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

  • Junxiong Wang, Debabrota Basu, Immanuel Trummer
  • [Paper]

• 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]

• 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]

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

  • Kenshi Abe, Junpei Komiyama, Atsushi Iwasaki
  • [Paper]

• Latent Planning via Expansive Tree Search (NIPS 2022)

  • Robert Gieselmann, Florian T. Pokorny
  • [Paper]

• Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization (NIPS 2022)

  • Lei Song, Ke Xue, Xiaobin Huang, Chao Qian
  • [Paper]

• Optimistic Tree Searches for Combinatorial Black-Box Optimization (NIPS 2022)

  • Cédric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou-Ammar, Jun Wang
  • [Paper]

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

  • Dilina Chandika Rajapakse, Douglas Leith
  • [Paper]

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]

• 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]

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

  • John Mern, Anil Yildiz, Lawrence Bush, Tapan Mukerji, Mykel J. Kochenderfer
  • [Paper]

• 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]

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

  • Felix Mohr, Viktor Bengs, Eyke Hüllermeier
  • [Paper]

• 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]

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

  • Xiufeng Yang, Tanuj Kr Aasawat, Kazuki Yoshizoe
  • [Paper]

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

  • Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
  • [Paper]

• 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]

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]

• 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]
  • [Code]

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

  • Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim
  • [Paper]
  • [Code]

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

  • Lars Buesing, Nicolas Heess, Theophane Weber
  • [Paper]

• 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]
  • [Code]

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

  • Johannes Fischer, Ömer Sahin Tas
  • [Paper]
  • [Code]

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

  • Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
  • [Paper]

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

  • Feng Wu, Sarvapali D. Ramchurn
  • [Paper]

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

  • Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
  • [Paper]

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

  • Michael H. Lim, Claire Tomlin, Zachary N. Sunberg
  • [Paper]

• 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]

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

  • Guiliang Liu, Xu Li, Jiakang Wang, Mingming Sun, Ping Li
  • [Paper]

2019

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

  • Shangtong Zhang, Hengshuai Yao
  • [Paper]
  • [Code]

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

  • Christian Roberson, Katarina Sperduto
  • [Paper]
  • [Code]

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

  • Bo Chang, Shenyi Pan, Harry Joe
  • [Paper]
  • [Code]

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

  • Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai
  • [Paper]
  • [Code]

• 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]

• Monte Carlo Tree Search for Policy Optimization (IJCAI 2019)

  • Xiaobai Ma, Katherine Rose Driggs-Campbell, Zongzhang Zhang, Mykel J. Kochenderfer
  • [Paper]

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

  • Thomas Gabor, Jan Peter, Thomy Phan, Christian Meyer, Claudia Linnhoff-Popien
  • [Paper]
  • [Code]

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

  • Herilalaina Rakotoarison, Marc Schoenauer, Michèle Sebag
  • [Paper]
  • [Code]

• Multiple Policy Value Monte Carlo Tree Search (IJCAI 2019)

  • Li-Cheng Lan, Wei Li, Ting-Han Wei, I-Chen Wu
  • [Paper]

• 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]

2018

• Monte Carlo Methods for the Game Kingdomino (CIG 2018)

  • Magnus Gedda, Mikael Z. Lagerkvist, Martin Butler
  • [Paper]
  • [Code]
  • [Game Server]

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

  • Konstantinos Chatzilygeroudis, Vassilis Vassiliades, Jean-Baptiste Mouret
  • [Paper]
  • [Code]
  • [MCTS C++ Library]

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

  • Chenjun Xiao, Jincheng Mei, Martin Müller
  • [Paper]

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

  • Daniel R. Jiang, Emmanuel Ekwedike, Han Liu
  • [Paper]

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

  • Thayne T. Walker, Nathan R. Sturtevant, Ariel Felner
  • [Paper]

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

  • Chao Gao, Martin Müller, Ryan Hayward
  • [Paper]

• 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]

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

  • Zhuwen Li, Qifeng Chen, Vladlen Koltun
  • [Paper]

• 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]

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

  • Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber
  • [Paper]

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

  • Jongmin Lee, Geon-hyeong Kim, Pascal Poupart, Kee-Eung Kim
  • [Paper]

2017

• An Analysis of Monte Carlo Tree Search (AAAI 2017)

  • Steven James, George Dimitri Konidaris, Benjamin Rosman
  • [Paper]

• 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]

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

  • Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, Peter Stone
  • [Paper]

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

  • Sammie Katt, Frans A. Oliehoek, Christopher Amato
  • [Paper]

• Learning to Run Heuristics in Tree Search (IJCAI 2017)

  • Elias B. Khalil, Bistra Dilkina, George L. Nemhauser, Shabbir Ahmed, Yufen Shao
  • [Paper]

• 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]

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

  • Riccardo Sartea, Alessandro Farinelli
  • [Paper]

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

  • Emilie Kaufmann, Wouter M. Koolen
  • [Paper]

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

  • Thomas Anthony, Zheng Tian, David Barber
  • [Paper]

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

  • Shahaf S. Shperberg, Solomon Eyal Shimony, Ariel Felner
  • [Paper]

2016

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

  • Robert Arrington, Clay Langley, Steven Bogaerts
  • [Paper]

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

  • Bilal Kartal, Ernesto Nunes, Julio Godoy, Maria L. Gini
  • [Paper]

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

  • Olivier Canévet, François Fleuret
  • [Paper]

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

  • Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone
  • [Paper]

• 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]

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

  • Timothy Yee, Viliam Lisý, Michael H. Bowling
  • [Paper]

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

  • Yunlong Liu, Hexing Zhu, Yifeng Zeng, Zongxiong Dai
  • [Paper]

2015

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

  • Tat-Jun Chin, Pulak Purkait, Anders P. Eriksson, David Suter
  • [Paper]

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

  • Daniel Hennes, Dario Izzo
  • [Paper]

2014

• State Aggregation in Monte Carlo Tree Search (AAAI 2014)

  • Jesse Hostetler, Alan Fern, Tom Dietterich
  • [Paper]

• 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]

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

  • Jervis Pinto, Alan Fern
  • [Paper]

2013

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

  • Mohamed R. Amer, Sinisa Todorovic, Alan Fern, Song-Chun Zhu
  • [Paper]

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

  • Viliam Lisý, Vojtech Kovarík, Marc Lanctot, Branislav Bosanský
  • [Paper]

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

  • Aijun Bai, Feng Wu, Xiaoping Chen
  • [Paper]

2012

• Generalized Monte-Carlo Tree Search Extensions for General Game Playing (AAAI 2012)
  • Hilmar Finnsson
  • [Paper]

2011

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

  • Fan Xie, Hootan Nakhost, Martin Müller
  • [Paper]

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

  • Satomi Baba, Yongjoon Joe, Atsushi Iwasaki, Makoto Yokoo
  • [Paper]

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

  • Christopher D. Rosin
  • [Paper]

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

  • Joel Veness, Marc Lanctot, Michael H. Bowling
  • [Paper]

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

  • John Asmuth, Michael L. Littman
  • [Paper]

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]

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

  • Gerald Tesauro, V. T. Rajan, Richard Segal
  • [Paper]

2009

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

  • Paolo Ciancarini, Gian Piero Favini
  • [Paper]

• Bootstrapping from Game Tree Search (NIPS 2009)

  • Joel Veness, David Silver, William T. B. Uther, Alan Blair
  • [Paper]

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]

2007

• Bandit Algorithms for Tree Search (UAI 2007)
  • Pierre-Arnaud Coquelin, Rémi Munos
  • [Paper]

2006

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

  • Yew Jin Lim, Wee Sun Lee
  • [Paper]

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

  • Hideki Hirakawa
  • [Paper]

2005

• Game-Tree Search with Combinatorially Large Belief States (IJCAI 2005)
  • Austin Parker, Dana S. Nau, V. S. Subrahmanian
  • [Paper]

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]

2001

• Incomplete Tree Search using Adaptive Probing (IJCAI 2001)
  • Wheeler Ruml
  • [Paper]

1998

• KnightCap: A Chess Programm That Learns by Combining TD with Game-Tree Search (ICML 1998)
  • Jonathan Baxter, Andrew Tridgell, Lex Weaver
  • [Paper]

1988

• A Tree Search Algorithm for Target Detection in Image Sequences (CVPR 1988)
  • Steven D. Blostein, Thomas S. Huang
  • [Paper]

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License

• CC0 Universal

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