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2020 – today
- 2024
[c6]Tom Pepels
, Mark H. M. Winands:
Ancestor-Based α-β Bounds for Monte-Carlo Tree Search. CoG 2024: 1-4
2010 – 2019
- 2015
- [c5]Tom Pepels, Tristan Cazenave, Mark H. M. Winands:
Sequential Halving for Partially Observable Games. CGW/GIGA@IJCAI 2015: 16-29 - 2014
- [j2]Tom Pepels, Mark H. M. Winands, Marc Lanctot:
Real-Time Monte Carlo Tree Search in Ms Pac-Man. IEEE Trans. Comput. Intell. AI Games 6(3): 245-257 (2014) - [c4]Marc Lanctot, Mark H. M. Winands, Tom Pepels, Nathan R. Sturtevant:
Monte Carlo Tree Search with heuristic evaluations using implicit minimax backups. CIG 2014: 1-8 - [c3]Tom Pepels, Tristan Cazenave, Mark H. M. Winands, Marc Lanctot:
Minimizing Simple and Cumulative Regret in Monte-Carlo Tree Search. CGW@ECAI 2014: 1-15 - [c2]Tom Pepels, Mandy J. W. Tak, Marc Lanctot, Mark H. M. Winands:
Quality-based Rewards for Monte-Carlo Tree Search Simulations. ECAI 2014: 705-710 - [i1]Marc Lanctot, Mark H. M. Winands, Tom Pepels, Nathan R. Sturtevant:
Monte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups. CoRR abs/1406.0486 (2014) - 2012
- [j1]Tom Pepels:
The CIG'12 MS Pac-Man vs. Ghosts Competition. J. Int. Comput. Games Assoc. 35(4): 239-240 (2012) - [c1]Tom Pepels, Mark H. M. Winands:
Enhancements for Monte-Carlo Tree Search in Ms Pac-Man. CIG 2012: 265-272
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