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Martin Müller 0003
Person information
- affiliation: University of Alberta, Canada
- affiliation (former): Electrotechnical Laboratory Tsukuba, Japan
Other persons with the same name
- Martin Müller — disambiguation page
- Martin Müller 0001 — Universität des Saarlandes, Saarbrücken, Germany
- Martin Müller 0002 — Siemens AG, Munich, Germany
- Martin Müller 0004 — Trier University, Germany
- Martin Müller 0005 — Oldenburg University, Germany
- Martin Müller 0006 — University of Marburg, Germany
- Martin Müller 0007 — Braunschweig University of Technology, Germany
- Martin Müller 0008
— FHNW, University of Applied Sciences and Arts Northwestern, School of Architecture, Civil Engineering and Geomatics, Muttenz, Switzerland
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2020 – today
- 2024
- [c83]Farnaz Kohankhaki, Kiarash Aghakasiri, Hongming Zhang, Ting-Han Wei, Chao Gao, Martin Müller:
Monte Carlo Tree Search in the Presence of Transition Uncertainty. AAAI 2024: 20151-20158 - [c82]Md. Solimul Chowdhury, Martin Müller, Jia-Huai You:
Exploring Conflict Generating Decisions: Initial Results (Extended Abstract). SOCS 2024: 267-268 - [i16]Owen Randall, Martin Müller, Ting-Han Wei, Ryan Hayward:
Expected Work Search: Combining Win Rate and Proof Size Estimation. CoRR abs/2405.05594 (2024) - [i15]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Neural Network-based Information Set Weighting for Playing Reconnaissance Blind Chess. CoRR abs/2407.05864 (2024) - [i14]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets. CoRR abs/2407.05876 (2024) - [i13]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Learning With Generalised Card Representations for "Magic: The Gathering". CoRR abs/2407.05879 (2024) - [i12]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Contrastive Learning of Preferences with a Contextual InfoNCE Loss. CoRR abs/2407.05898 (2024) - 2023
- [c81]Quazi Asif Sadmine, Asmaul Husna, Martin Müller
:
Stockfish or Leela Chess Zero? A Comparison Against Endgame Tablebases. ACG 2023: 26-35 - [c80]Haoyu Du, Ting-Han Wei, Martin Müller
:
Solving NoGo on Small Rectangular Boards. ACG 2023: 39-49 - [c79]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Weighting Information Sets with Siamese Neural Networks in Reconnaissance Blind Chess. CoG 2023: 1-8 - [c78]Jiuqi Wang, Martin Müller, Jonathan Schaeffer:
Deep Dive on Checkers Endgame Data. CoG 2023: 1-8 - [c77]Hongming Zhang, Chenjun Xiao, Han Wang, Jun Jin, Bo Xu, Martin Müller:
Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay. ICLR 2023 - [i11]Farnaz Kohankhaki, Kiarash Aghakasiri, Hongming Zhang, Ting-Han Wei, Chao Gao, Martin Müller:
Monte Carlo Tree Search in the Presence of Transition Uncertainty. CoRR abs/2312.11348 (2023) - 2022
- [c76]Owen Randall, Ting-Han Wei, Ryan Hayward, Martin Müller:
Improving Search in Go Using Bounded Static Safety. CG 2022: 14-23 - [c75]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess. CoG 2022: 608-611 - [i10]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability. CoRR abs/2204.09462 (2022) - [i9]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess. CoRR abs/2208.02029 (2022) - 2021
- [c74]Rejwana Haque, Ting-Han Wei, Martin Müller
:
On the Road to Perfection? Evaluating Leela Chess Zero Against Endgame Tablebases. ACG 2021: 142-152 - [c73]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking. CoG 2021: 1-8 - [c72]Ryan W. Gardner, Gino Perrotta, Anvay Shah, Shivaram Kalyanakrishnan, Kevin A. Wang, Gregory Clark, Timo Bertram, Johannes Fürnkranz, Martin Müller, Brady P. Garrison, Prithviraj Dasgupta, Saeid Rezaei:
The Machine Reconnaissance Blind Chess Tournament of NeurIPS 2022. NeurIPS (Competition and Demos) 2021: 119-132 - [i8]Md. Solimul Chowdhury, Martin Müller, Jia-Huai You:
A Deep Dive into Conflict Generating Decisions. CoRR abs/2105.04595 (2021) - [i7]Timo Bertram, Johannes Fürnkranz, Martin Müller:
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking. CoRR abs/2105.11864 (2021) - [i6]Timo Bertram, Johannes Fürnkranz, Martin Müller:
A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems. CoRR abs/2107.04438 (2021) - [i5]Hongming Zhang, Ke Sun, Bo Xu, Linglong Kong, Martin Müller:
A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning. CoRR abs/2109.09889 (2021) - 2020
- [c71]Md. Solimul Chowdhury, Martin Müller, Jia-Huai You:
Guiding CDCL SAT Search via Random Exploration amid Conflict Depression. AAAI 2020: 1428-1435
2010 – 2019
- 2019
- [c70]Md. Solimul Chowdhury, Martin Müller, Jia-Huai You:
Exploiting Glue Clauses to Design Effective CDCL Branching Heuristics. CP 2019: 126-143 - [c69]Jincheng Mei, Chenjun Xiao, Ruitong Huang, Dale Schuurmans, Martin Müller:
On Principled Entropy Exploration in Policy Optimization. IJCAI 2019: 3130-3136 - [c68]Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller:
Maximum Entropy Monte-Carlo Planning. NeurIPS 2019: 9516-9524 - [r1]Kazuki Yoshizoe, Martin Müller:
Computer Go. Encyclopedia of Computer Graphics and Games 2019 - [i4]Md. Solimul Chowdhury, Martin Müller, Jia-Huai You:
Characterization of Glue Variables in CDCL SAT Solving. CoRR abs/1904.11106 (2019) - [i3]Chenjun Xiao, Yifan Wu, Chen Ma, Dale Schuurmans, Martin Müller:
Learning to Combat Compounding-Error in Model-Based Reinforcement Learning. CoRR abs/1912.11206 (2019) - 2018
- [j21]Chao Gao, Siqi Yan, Ryan Hayward, Martin Müller:
A transferable neural network for Hex. J. Int. Comput. Games Assoc. 40(3): 224-233 (2018) - [j20]I-Chen Wu
, Chang-Shing Lee, Yuandong Tian, Martin Müller:
Guest Editorial Special Issue on Deep/Reinforcement Learning and Games. IEEE Trans. Games 10(4): 333-335 (2018) - [j19]Chao Gao
, Ryan Hayward, Martin Müller
:
Move Prediction Using Deep Convolutional Neural Networks in Hex. IEEE Trans. Games 10(4): 336-343 (2018) - [c67]Chenjun Xiao, Jincheng Mei, Martin Müller:
Memory-Augmented Monte Carlo Tree Search. AAAI 2018: 1455-1462 - [c66]Md. Solimul Chowdhury, Martin Müller, Jia-Huai You:
Preliminary Results on Exploration-Driven Satisfiability Solving. AAAI 2018: 8069-8070 - [c65]Gaojian Fan, Robert Holte, Martin Müller:
MS-Lite: A Lightweight, Complementary Merge-and-Shrink Method. ICAPS 2018: 74-82 - [c64]Chao Gao, Martin Müller, Ryan Hayward:
Adversarial Policy Gradient for Alternating Markov Games. ICLR (Workshop) 2018 - [c63]Farhad Haqiqat, Martin Müller:
Analyzing the Impact of Knowledge and Search in Monte Carlo Tree Search in Go. CGW@IJCAI 2018: 127-146 - [c62]Chao Gao, Martin Müller, Ryan Hayward:
Three-Head Neural Network Architecture for Monte Carlo Tree Search. IJCAI 2018: 3762-3768 - 2017
- [c61]Gaojian Fan, Martin Müller, Robert Holte:
The Two-Edged Nature of Diverse Action Costs. ICAPS 2017: 98-106 - [c60]Ruitong Huang, Mohammad M. Ajallooeian, Csaba Szepesvári, Martin Müller:
Structured Best Arm Identification with Fixed Confidence. ALT 2017: 593-616 - [c59]Chao Gao, Martin Müller, Ryan Hayward:
Focused Depth-first Proof Number Search using Convolutional Neural Networks for the Game of Hex. IJCAI 2017: 3668-3674 - [c58]Gaojian Fan, Martin Müller, Robert Holte:
Additive Merge-and-Shrink Heuristics for Diverse Action Costs. IJCAI 2017: 4287-4293 - [i2]Ruitong Huang, Mohammad M. Ajallooeian, Csaba Szepesvári, Martin Müller:
Structured Best Arm Identification with Fixed Confidence. CoRR abs/1706.05198 (2017) - 2016
- [c57]Chenjun Xiao, Martin Müller:
Factorization Ranking Model for Move Prediction in the Game of Go. AAAI 2016: 1359-1365 - [c56]Chenjun Xiao, Martin Müller:
Integrating Factorization Ranked Features in MCTS: An Experimental Study. CGW@IJCAI 2016: 34-43 - 2015
- [j18]Jiaxing Song, Martin Müller:
An Enhanced Solver for the Game of Amazons. IEEE Trans. Comput. Intell. AI Games 7(1): 16-27 (2015) - [c55]Yeqin Zhang, Martin Müller:
TDS+: Improving Temperature Discovery Search. AAAI 2015: 1241-1247 - [c54]Fan Xie, Martin Müller, Robert Holte:
Understanding and Improving Local Exploration for GBFS. ICAPS 2015: 244-248 - [c53]Martin Müller:
Keynote speech III: Computer go research - The challenges ahead. CIG 2015: 18 - 2014
- [j17]Hootan Nakhost, Martin Müller:
Towards a theory of random walk planning: Regress factors, fair homogeneous graphs and extensions. AI Commun. 27(4): 329-344 (2014) - [c52]Fan Xie, Martin Müller, Robert Holte:
Adding Local Exploration to Greedy Best-First Search in Satisficing Planning. AAAI 2014: 2388-2394 - [c51]Fan Xie, Martin Müller, Robert Holte, Tatsuya Imai:
Type-Based Exploration with Multiple Search Queues for Satisficing Planning. AAAI 2014: 2395-2402 - [c50]Gaojian Fan, Martin Müller, Robert Holte:
Non-Linear Merging Strategies for Merge-and-Shrink Based on Variable Interactions. SOCS 2014: 53-61 - 2013
- [c49]David Silver, Richard S. Sutton, Martin Müller:
Temporal-Difference Search in Computer Go. ICAPS 2013 - [c48]Fan Xie, Richard Anthony Valenzano, Martin Müller:
Better Time Constrained Search via Randomization and Postprocessing. ICAPS 2013 - [c47]Shih-Chieh Huang, Martin Müller:
Investigating the Limits of Monte-Carlo Tree Search Methods in Computer Go. Computers and Games 2013: 39-48 - [c46]Shih-Chieh Huang, Broderick Arneson, Ryan B. Hayward, Martin Müller, Jakub Pawlewicz
:
MoHex 2.0: A Pattern-Based MCTS Hex Player. Computers and Games 2013: 60-71 - [c45]Sumudu Fernando, Martin Müller:
Analyzing Simulations in Monte-Carlo Tree Search for the Game of Go. Computers and Games 2013: 72-83 - [c44]Hootan Nakhost, Martin Müller:
Towards a Second Generation Random Walk Planner: An Experimental Exploration. IJCAI 2013: 2336-2342 - 2012
- [j16]Akihiro Kishimoto, Mark H. M. Winands, Martin Müller, Jahn-Takeshi Saito:
Game-Tree Search Using Proof Numbers: The First Twenty Years. J. Int. Comput. Games Assoc. 35(3): 131-156 (2012) - [j15]David Silver, Richard S. Sutton, Martin Müller:
Temporal-difference search in computer Go. Mach. Learn. 87(2): 183-219 (2012) - [c43]Hootan Nakhost, Jörg Hoffmann, Martin Müller:
Resource-Constrained Planning: A Monte Carlo Random Walk Approach. ICAPS 2012 - [c42]Fan Xie, Hootan Nakhost, Martin Müller:
Planning Via Random Walk-Driven Local Search. ICAPS 2012 - [c41]Richard Anthony Valenzano, Hootan Nakhost, Martin Müller, Jonathan Schaeffer, Nathan R. Sturtevant:
ArvandHerd: Parallel Planning with a Portfolio. ECAI 2012: 786-791 - [c40]James Styles, Holger H. Hoos, Martin Müller:
Automatically Configuring Algorithms for Scaling Performance. LION 2012: 205-219 - [c39]Hootan Nakhost, Martin Müller:
A Theoretical Framework for Studying Random Walk Planning. SOCS 2012: 57-64 - 2011
- [c38]Fan Xie, Hootan Nakhost, Martin Müller:
A Local Monte Carlo Tree Search Approach in Deterministic Planning. AAAI 2011 - [c37]Gabriel Van Eyck, Martin Müller:
Revisiting Move Groups in Monte-Carlo Tree Search. ACG 2011: 13-23 - [c36]Henry Brausen, Ryan B. Hayward, Martin Müller, Abdul Qadir, David Spies:
Blunder Cost in Go and Hex. ACG 2011: 220-229 - [i1]Adi Botea, Markus Enzenberger, Martin Müller, Jonathan Schaeffer:
Macro-FF: Improving AI Planning with Automatically Learned Macro-Operators. CoRR abs/1109.2154 (2011) - 2010
- [j14]Chang-Shing Lee
, Martin Müller, Olivier Teytaud:
Special Issue on Monte Carlo Techniques and Computer Go. IEEE Trans. Comput. Intell. AI Games 2(4): 225-228 (2010) - [j13]Markus Enzenberger, Martin Müller, Broderick Arneson, R. Segal:
Fuego - An Open-Source Framework for Board Games and Go Engine Based on Monte Carlo Tree Search. IEEE Trans. Comput. Intell. AI Games 2(4): 259-270 (2010) - [c35]Hootan Nakhost, Martin Müller:
Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement. ICAPS 2010: 121-128 - [c34]David Tom, Martin Müller:
Computational Experiments with the RAVE Heuristic. Computers and Games 2010: 69-80 - [c33]Neil Burch, Robert C. Holte, Martin Müller, David O'Connell, Jonathan Schaeffer:
Automating Layouts of Sewers in Subdivisions. ECAI 2010: 655-660 - [c32]Hootan Nakhost, Jörg Hoffmann, Martin Müller:
Improving Local Search for Resource-Constrained Planning. SOCS 2010: 81-82
2000 – 2009
- 2009
- [c31]Markus Enzenberger, Martin Müller:
A Lock-Free Multithreaded Monte-Carlo Tree Search Algorithm. ACG 2009: 14-20 - [c30]David Tom, Martin Müller:
A Study of UCT and Its Enhancements in an Artificial Game. ACG 2009: 55-64 - [c29]Hootan Nakhost, Martin Müller:
Monte-Carlo Exploration for Deterministic Planning. IJCAI 2009: 1766-1771 - 2008
- [c28]Ling Zhao, Martin Müller:
Using Artificial Boundaries in the Game of Go. Computers and Games 2008: 81-91 - [c27]Xiaozhen Niu, Martin Müller:
An Improved Safety Solver in Go Using Partial Regions. Computers and Games 2008: 102-112 - [c26]Akihiro Kishimoto, Martin Müller:
About the Completeness of Depth-First Proof-Number Search. Computers and Games 2008: 146-156 - [c25]David Silver, Richard S. Sutton, Martin Müller:
Sample-based learning and search with permanent and transient memories. ICML 2008: 968-975 - 2007
- [c24]David Silver, Richard S. Sutton, Martin Müller:
Reinforcement Learning of Local Shape in the Game of Go. IJCAI 2007: 1053-1058 - [c23]Adi Botea, Martin Müller, Jonathan Schaeffer:
Fast Planning with Iterative Macros. IJCAI 2007: 1828-1833 - [c22]Kazuki Yoshizoe, Akihiro Kishimoto, Martin Müller:
Lambda Depth-First Proof Number Search and Its Application to Go. IJCAI 2007: 2404-2409 - 2006
- [c21]Xiaozhen Niu, Akihiro Kishimoto, Martin Müller:
Recognizing Seki in Computer Go. ACG 2006: 88-103 - [c20]Ling Zhao, Martin Müller:
Solving Probabilistic Combinatorial Games. ACG 2006: 225-238 - [c19]Xiaozhen Niu, Martin Müller:
An Open Boundary Safety-of-Territory Solver for the Game of Go. Computers and Games 2006: 37-49 - 2005
- [j12]Akihiro Kishimoto, Martin Müller:
A solution to the GHI problem for depth-first proof-number search. Inf. Sci. 175(4): 296-314 (2005) - [j11]Adi Botea, Markus Enzenberger, Martin Müller, Jonathan Schaeffer:
Macro-FF: Improving AI Planning with Automatically Learned Macro-Operators. J. Artif. Intell. Res. 24: 581-621 (2005) - [c18]Akihiro Kishimoto, Martin Müller:
Search versus Knowledge for Solving Life and Death Problems in Go. AAAI 2005: 1374-1379 - [c17]Adi Botea, Martin Müller, Jonathan Schaeffer:
Learning Partial-Order Macros from Solutions. ICAPS 2005: 231-240 - [c16]Akihiro Kishimoto, Martin Müller:
Dynamic Decomposition Search: A Divide and Conquer Approach and its Application to the One-Eye Problem in Go. CIG 2005 - [c15]Jonathan Schaeffer, Yngvi Björnsson, Neil Burch, Akihiro Kishimoto, Martin Müller, Robert Lake, Paul Lu, Steve Sutphen:
Solving Checkers. IJCAI 2005: 292-297 - 2004
- [j10]Jianjun Zhou, Martin Müller:
Solving Systems of Difference Constraints Incrementally with Bidirectional Search. Algorithmica 39(3): 255-274 (2004) - [j9]Adi Botea, Martin Müller, Jonathan Schaeffer:
Near Optimal Hierarchical Path-Finding. J. Game Dev. 1(1): 1-30 (2004) - [c14]Akihiro Kishimoto, Martin Müller:
A General Solution to the Graph History Interaction Problem. AAAI 2004: 644-649 - [c13]Martin Müller, Markus Enzenberger, Jonathan Schaeffer:
Temperature Discovery Search. AAAI 2004: 658-663 - [c12]Adi Botea, Martin Müller, Jonathan Schaeffer:
Using Component Abstraction for Automatic Generation of Macro-Actions. ICAPS 2004: 181-190 - [c11]Xiaozhen Niu, Martin Müller:
An Improved Safety Solver for Computer Go. Computers and Games 2004: 97-112 - [c10]Martin Müller, Zhichao Li:
Locally Informed Global Search for Sums of Combinatorial Games. Computers and Games 2004: 273-284 - [c9]Ling Zhao, Martin Müller:
Game-SAT: A Preliminary Report. SAT 2004 - 2003
- [j8]Jianjun Zhou, Martin Müller:
Depth-First Discovery Algorithm for incremental topological sorting of directed acyclic graphs. Inf. Process. Lett. 88(4): 195-200 (2003) - [j7]Martin Müller:
Conditional combinatorial games and their application to analyzing capturing races in Go. Inf. Sci. 154(3-4): 189-202 (2003) - [c8]Akihiro Kishimoto, Martin Müller:
DF-PN in Go: An Application to the One-Eye Problem. ACG 2003: 125-142 - [e1]Jonathan Schaeffer, Martin Müller, Yngvi Björnsson:
Computers and Games, Third International Conference, CG 2002, Edmonton, Canada, July 25-27, 2002, Revised Papers. Lecture Notes in Computer Science 2883, Springer 2003, ISBN 3-540-20545-4 [contents] - 2002
- [j6]Martin Müller:
Computer Go. Artif. Intell. 134(1-2): 145-179 (2002) - [j5]Martin Müller:
Position Evaluation in Computer Go. J. Int. Comput. Games Assoc. 25(4): 219-228 (2002) - [c7]Martin Müller:
Proof-Set Search. Computers and Games 2002: 88-107 - [c6]Adi Botea, Martin Müller, Jonathan Schaeffer:
Using Abstraction for Planning in Sokoban. Computers and Games 2002: 360-375 - [c5]Martin Müller:
A Generalized Framework for Analyzing Capturing Races in Go. JCIS 2002: 469-472 - 2001
- [j4]Martin Müller:
Partial order bounding: A new approach to evaluation in game tree search. Artif. Intell. 129(1-2): 279-311 (2001) - [j3]Martin Müller:
Global and local game tree search. Inf. Sci. 135(3-4): 187-206 (2001) - 2000
- [j2]Hiroyuki Iida, Martin Müller:
Report on the second Open Computer-Amazons Championship. J. Int. Comput. Games Assoc. 23(1): 51-54 (2000) - [c4]Martin Müller:
Review: Computer Go 1984-2000. Computers and Games 2000: 405-413
1990 – 1999
- 1999
- [j1]Martin Müller:
Computer Go: A Research Agenda. J. Int. Comput. Games Assoc. 22(2): 104-112 (1999) - [c3]Martin Müller:
Decomposition Search: A Combinatorial Games Approach to Game Tree Search, with Applications to Solving Go Endgames. IJCAI 1999: 578-583 - 1998
- [c2]Martin Müller:
Computer Go: A Research Agenda. Computers and Games 1998: 252-264 - 1991
- [c1]Anders Kierulf, Ralph Gasser, Peter M. Geiser, Martin Müller, Jürg Nievergelt, Christoph Wirth:
Every Interactive System Evolves into Hyperspace: The Case of the Smart Game Board. Hypertext/Hypermedia 1991: 174-180
Coauthor Index
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