Dennis Soemers (D.J.N.J.)
Research profile
My primary areas of research interest include artificial intelligence (AI) for sequential decision-making problems (e.g., search and reinforcement learning algorithms), Transfer Learning and generalisation in AI, AI in and for games, multi-armed bandits, and adaptation to adversaries.
Key publications
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Soemers, D. J. N. J. (2023). Learning state-action features for general game playing. [Doctoral Thesis, Maastricht University]. Maastricht University. https://doi.org/10.26481/dis.20230425dsMore information about this publication
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Soemers, D. J. N. J., Bams, G., Persoon, M., Rietjens, M., Sladić, D., Stefanov, S., Driessens, K., & Winands, M. H. M. (2024). Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games. In 2024 IEEE Conference on Games (CoG) (pp. 1-4). IEEE. https://doi.org/10.1109/CoG60054.2024.10645675More information about this publication
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Soemers, D. J. N. J., Samothrakis, S., Piette, E., & Stephenson, M. (2023). Extracting tactics learned from self-play in general games. Information Sciences, 624, 277-298. https://doi.org/10.1016/j.ins.2022.12.080More information about this publication