DKE research theme

Game AI & Search (GAIS)

Search is a key reasoning technique. Research in Game Artificial Intelligence (AI) & Search therefore helps to increase the quality of automated decision-making, whether this is used to make the final decision autonomously or to provide a human with a range of sensible options.

This work is complemented by the Digital Ludeme Project, funded by an ERC grant of €2 million. The project introduces the field of Digital Archaeoludology, which combines computational and historical analyses of traditional games.

Highlighted publications

  • Baier, H., & Winands, M. H. M. (2018). MCTS-Minimax Hybrids with State Evaluations. Journal of Artificial Intelligence Research, 62, 193-231. https://doi.org/10.1613/jair.1.11208
  • Browne, C. (2018). Modern Techniques for Ancient Games. In 2018 IEEE Conference on Computational Intelligence and Games, CIG 2018, Maastricht, The Netherlands, August 14-17, 2018 (pp. 1-8)
  • Browne, C., & Piette, E. (2019). Digital Archaeoludology. In Computer Applications and Quantitative Methods in Archaeology : (CAA'19)
  • Crist, W. (2021). Debunking the Diffusion of Senet. Board Game Studies Journal, 15:1, pp. 13– 27
  • Gaina, R. D., Couëtoux, A., Soemers, D. J. N. J., Winands, M. H. M., Vodopivec, T., Kirchgessner, F., Liu, J., Lucas, S. M., & Diego Perez-Liebana, D. (2018). The 2016 Two-Player GVGAI Competition. IEEE Transactions on Games, 10(2), 209-220. https://doi.org/10.1109/TCIAIG.2017.2771241
  • Piette, E., Soemers, D. J. N. J., Stephenson, M., Sironi, C. F., Winands, M. H. M., & Browne, C. (2020). Ludii - The Ludemic General Game System. In G. De Giacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarín, & J. Lang (Eds.), ECAI 2020 : 24th European Conference on Artificial Intelligence (Vol. 325, pp. 411-418). IOS Press. Frontiers in Artificial Intelligence and Applications https://doi.org/10.3233/FAIA200120
  • Rossi, L., Winands, M. H. M., & Butenweg, C. (2021). Monte Carlo Tree Search as an intelligent search tool in structural design problems. Engineering with Computers. https://doi.org/10.1007/s00366-021-01338-2
  • Sironi, C. F., Liu, J., & Winands, M. H. M. (2020). Self-Adaptive Monte Carlo Tree Search in General Game Playing. IEEE Transactions on Games, 12(2), 132-144. https://doi.org/10.1109/TG.2018.2884768
  • Soemers, D. J. N. J., Brys, T., Driessens, K., Winands, M. H. M., & Nowé, A. (2018). Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2-7, 2018: The Thirtieth AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-18) (pp. 7831-7836). AAAI Press. https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16183
  • Stephenson, M., Renz, J., & Ge, X. (2020). The computational complexity of Angry Birds. Artificial Intelligence, 280, [103232]. https://doi.org/10.1016/j.artint.2019.103232

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