Timo Bertram

CoRR, 2024

Neural Network-based Information Set Weighting for Playing Reconnaissance Blind Chess.

[BibT_eX]

[DOI]

CoRR, 2024

Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets.

[BibT_eX]

[DOI]

Proceedings of the KI 2024: Advances in Artificial Intelligence, 2024

Learning With Generalised Card Representations for "Magic: The Gathering".

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Games, 2024

2023

Weighting Information Sets with Siamese Neural Networks in Reconnaissance Blind Chess.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Games, 2023

2022

Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability.

[BibT_eX]

[DOI]

CoRR, 2022

Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Games, CoG 2022, Beijing, 2022

2021

A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems.

[BibT_eX]

[DOI]

CoRR, 2021

The Machine Reconnaissance Blind Chess Tournament of NeurIPS 2022.

[BibT_eX]

[DOI]

Ryan W. Gardner

Gino Perrotta

Anvay Shah

Shivaram Kalyanakrishnan

Proceedings of the NeurIPS 2022 Competition Track, 2021

Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking.

[BibT_eX]

[DOI]