2024
Neural Network-based Information Set Weighting for Playing Reconnaissance Blind Chess
Timo Bertram, Johannes Fürnkranz, Martin Müller
IEEE Transactions on Games 2024
Contrastive Learning of Preferences with a Contextual InfoNCE Loss
Timo Bertram, Johannes Fürnkranz, Martin Müller
arXiv preprint
Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets
Timo Bertram, Johannes Fürnkranz, Martin Müller
KI 2024: Advances in Artificial Intelligence
Learning With Generalised Card Representations for “Magic: The Gathering”
Timo Bertram, Johannes Fürnkranz, Martin Müller
Proceedings of the IEEE Conference on Games (CoG 2024)
Best student paper award
2023
The machine reconnaissance blind chess tournament of NeurIPS 2022
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
NeurIPS 2022 Competition Track
Weighting Information Sets with Siamese Neural Networks in Reconnaissance Blind Chess
Timo Bertram, Johannes Fürnkranz, Martin Müller
Proceedings of the IEEE Conference on Games (CoG 2023)
2022
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess
Timo Bertram, Johannes Fürnkranz, Martin Müller
Proceedings of the IEEE Conference on Games (CoG 2022)
Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability
Timo Bertram, Johannes Fürnkranz, Martin Müller
arXiv preprint
2021
A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems
Timo Bertram, Johannes Fürnkranz, Martin Müller
ICML SubsetML: From Theory to Practice
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking
Timo Bertram, Johannes Fürnkranz, Martin Müller
Proceedings of the IEEE Conference on Games (CoG 2021)
Best paper award