Publications by Müller, Martin
In Journal (refereed)
1. | I. Wu, C. Lee, Y. Tian, M. Müller. "Guest editorial". IEEE Transactions on Games, 10(4), pp 333-335, December 2018. |
2. | C. Gao, R. Hayward, M. Müller. "Move Prediction Using Deep Convolutional Neural Networks in Hex". IEEE Transactions on Games, 10(4), pp 336 - 343, December 2018. |
3. | C. Gao, S. Yan, R. Hayward, M. Müller. "A Transferable Neural Network for Hex". Journal of the International Computer Games Association (ICGA), 40(3), pp 224-233, June 2018. |
4. | J. Schaeffer, M. Müller, A. Kishimoto. "Go-bot, Go". IEEE Spectrum, 51(7), pp 48-53, July 2014. |
5. | J. Song, M. Müller. "An Enhanced Solver for the Game of Amazons". IEEE Transactions on Computational Intelligence and AI in Games, 7(1), pp 16-27, March 2014. |
6. | H. Nakhost, M. Müller. "Towards a Theory of Random Walk Planning: Regress Factors, Fair Homogeneous Graphs, and Extensions". AI Communications, 27(4), pp 329-344, January 2014. |
7. | S. Fernando, M. Müller. "Analyzing Simulations in Monte Carlo Tree Search for the Game of Go". Computers and Games, pp 72-83, January 2013. |
8. | S. Huang, B. Arneson, R. Hayward, M. Müller. "MoHex 2.0: a pattern-based MCTS Hex player". Computers and Games, pp 39-48, January 2013. |
In Conference (refereed)
9. | M. Chowdhury, M. Müller, J. You. "Guiding CDCL SAT Search via Random Exploration amid Conflict Depression". National Conference on Artificial Intelligence (AAAI), pp 1428-1435, February 2020. |
10. | C. Xiao, J. Mei, R. Huang, D. Schuurmans, M. Müller. "Maximum Entropy Monte-Carlo Planning". Neural Information Processing Systems (NIPS), pp 9516-9524, December 2019. |
11. | M. Chowdhury, M. Müller, J. You. "Exploiting Glue Clauses to Design Effective CDCL Branching Heuristics". International Conference on Principles and Practice of Constraint Programming (CP), Stamford, USA, (ed: Schiex T., de Givry S.), pp 126-143, September 2019. |
12. | J. Mei, C. Xiao, R. Huang, D. Schuurmans, M. Müller. "On Principled Entropy Exploration in Policy Optimization". International Joint Conference on Artificial Intelligence (IJCAI), (ed: Sarit Kraus), pp 3130-3136, August 2019. |
13. | C. Gao, M. Müller, R. Hayward. "Three-Head Neural Network Architecture for Monte Carlo Tree Search". International Joint Conference on Artificial Intelligence (IJCAI), (ed: Jérôme Lang), pp 3762-3768, July 2018. |
14. | M. Chowdhury, M. Müller, J. You. "GrandTour-obs Puzzle as a SAT Benchmark". SAT Competition, (ed: Heule , M J H , Järvisalo , M J & Suda , M), pp 59-60, June 2018. |
15. | G. Fan, R. Holte, M. Müller. "MS-Lite: A Lightweight, Complementary Merge-and-Shrink Method". ICAPS, pp 74-82, June 2018. |
16. | C. Gao, M. Müller, R. Hayward. "Adversarial Policy Gradient for Alternating Markov Games". International Conference on Learning Representations, pp n/a, April 2018. |
17. | C. Xiao, J. Mei, M. Müller. "Memory-augmented Monte Carlo Tree Search". National Conference on Artificial Intelligence (AAAI), (ed: Sheila A. McIlraith, Kilian Q. Weinberger), pp 1455-1462, February 2018. |
18. | R. Huang, M. Ajallooeian, C. Szepesvari, M. Müller. "Structured Best Arm Identification with Fixed Confidence". Algorithmic Learning Theory (ALT), (ed: Steve Hanneke, Lev Reyzin), pp 593-616, October 2017. |
19. | G. Fan, M. Müller, R. Holte. "Additive Merge-and-Shrink Heuristics for Diverse Action Costs". International Joint Conference on Artificial Intelligence (IJCAI), (ed: Carles Sierra), pp 4287-4293, August 2017. |
20. | C. Gao, M. Müller, R. Hayward. "Focused Depth-first Proof Number Search using Convolutional Neural Networks for the Game of Hex". International Joint Conference on Artificial Intelligence (IJCAI), (ed: Carles Sierra), pp 3668-3674, August 2017. |
21. | G. Fan, M. Müller, R. Holte. "The Two-Edged Nature of Diverse Action Costs". ICAPS, (ed: Laura Barbulescu, Jeremy Frank, Mausam, Stephen F. Smith), pp 98-106, June 2017. |
22. | C. Xiao, M. Müller. "Factorization Ranking Model for Move Prediction in the Game of Go". National Conference on Artificial Intelligence (AAAI), (ed: Dale Schuurmans, Michael P. Wellman), pp 1359-1365, February 2016. |
23. | F. Xie, M. Müller, R. Holte. "Understanding and Improving Local Exploration for GBFS". ICAPS, (ed: Ronen I. Brafman, Carmel Domshlak, Patrik Haslum, Shlomo Zilberstein), pp 244-248, June 2015. |
24. | Y. Zhang, M. Müller. "TDS+: Improving Temperature Discovery Search". National Conference on Artificial Intelligence (AAAI), (ed: Blai Bonet, Sven Koenig), pp 1241-1247, January 2015. |
25. | G. Fan, M. Müller, R. Holte. "Non-Linear Merging Strategies for Merge-and-Shrink Based on Variable Interactions". Symposium on Combinatorial Search, (ed: Stefan Edelkamp, Roman Barták:), pp 53-61, August 2014. |
26. | F. Xie, M. Müller, R. Holte. "Adding local exploration to greedy best-first search for satisficing planning". National Conference on Artificial Intelligence (AAAI), (ed: Carla E. Brodley, Peter Stone), pp 2388-2394, July 2014. |
27. | F. Xie, M. Müller, R. Holte, T. Imai. "Type-based exploration for satisficing planning with multiple search queues". National Conference on Artificial Intelligence (AAAI), (ed: Carla E. Brodley, Peter Stone), pp 2395-2402, June 2014. |
28. | H. Nakhost, M. Müller. "Towards a Second Generation Random Walk Planner: an Experimental Exploration". International Joint Conference on Artificial Intelligence (IJCAI), (ed: Francesca Rossi), pp 2336-2342, August 2013. |
29. | F. Xie, R. Valenzano, M. Müller. "Better Time Constrained Search via Randomization and Postprocessing". ICAPS, (ed: Daniel Borrajo, Subbarao Kambhampati, Angelo Oddi, Simone Fratini), pp 269-277, June 2013. |
30. | D. Silver, R. Sutton, M. Müller. "Temporal-Difference Search in Computer Go". ICAPS, (ed: Daniel Borrajo, Subbarao Kambhampati, Angelo Oddi, Simone Fratini), pp 486-487, June 2013. |
In Workshop
31. | C. Xiao, Y. Wu, D. Schuurmans, M. Müller. "Adaptive Planning Horizon for Model-Based Reinforcement Learning". NeurIPS Deep RL Workshops, December 2019. |
32. | C. Xiao, Y. Wu, C. Ma, D. Schuurmans, M. Müller. "Learning to Combat Compounding-Error in Model-Based Reinforcement Learning". NeurIPS Deep RL Workshops, December 2019. |
33. | F. Haqiqat, M. Müller. "Analyzing the impact of knowledge and search in Monte Carlo Tree Search in Go". Workshop on Computer Games (CGW), Springer, 1017, pp 127-146, July 2018. |
34. | C. Xiao, M. Müller. "Integrating Factorization Ranked Features in MCTS: an Experimental Study". Workshop on Computer Games (CGW), Springer, Cham, (ed: Cazenave T., Winands M., Edelkamp S., Schiffel S., Thielscher M., Togelius J.), 705, pp 34-43, July 2016. |
35. | W. Chen, M. Müller. "Continuous Arvand: Motion Planning with Monte Carlo Random Walks". Workshop on Planning and Robotics, pp 23-34, June 2015. |
Other Categories
36. | M. Chowdhury, M. Müller, J. You. "Characterization of Glue Variables in CDCL SAT Solving". Technical Report, University of Alberta, (9), April 2019. |
37. | K. Yoshizoe, M. Müller. "Computer Go". Encyclopedia of Computer Graphics and Games, Springer International, (ed: N. Lee), pp 1-13, February 2016. |
38. | F. Xie, M. Müller, R. Holte. "Jasper: the art of exploration in greedy best first search". The Eighth International Planning Competition, (ed: M. Vallati, L. Chrpa, and T. McCluskey), pp 39-42, June 2014. |
39. | F. Xie, R. Valenzano, M. Müller. "Better Time Constrained Search via Randomization and Postprocessing". Technical Report, University of Alberta, (TR 13-02), January 2013. |
40. | C. Hunt, M. Müller. "Fuegito: an Educational Software Package for Game Tree Search". Technical Report, University of Alberta, (TR13-03), January 2013. |