This special session is organised in association with the IEEE CIS Games Technical Committee (GTC).
Games are an ideal domain to study computational intelligence (CI) methods because they provide affordable, competitive, dynamic, reproducible environments suitable for testing new search algorithms, pattern-based evaluation methods, or learning concepts. Games scale from simple problems for developing algorithms to incredibly hard problems for testing algorithms to the limit. They are also interesting to observe, fun to play, and very attractive to students. Additionally, there is great potential for CI methods to improve the design and development of both computer games as well as tabletop games, board games, and puzzles. This special session aims at gathering leaders and neophytes in games research as well as practitioners in this field who research applications of computational intelligence methods to computer games.
In general, papers are welcome that consider all kinds of applications of methods (evolutionary computation, supervised learning, unsupervised learning, (deep) reinforcement learning, fuzzy systems, game-tree search, rolling horizon algorithms, MCTS, etc.) to games (card games, board games, mathematical games, action games, strategy games, role-playing games, arcade games, serious games, etc.).
Please note that the list below serves as a rough guide. The dates may be changed due to changes by the organizing committee. You can find the latest information at: https://wcci2022.org/call-for-papers/.
|31 January 2022||Paper Submission Deadline|
|26 April 2022||Paper Acceptance Notification|
|23 May 2022||Final Paper Submission Deadline|
|TBA||Early Registration Deadline|
Alexander Dockhorn is post-doctoral research associate at the Otto von Guericke University of Magdeburg. He received his PhD at the Otto von Guericke University in Magdeburg in 2020, after which he continued his research on games at the Game AI Lab of the Queen Mary University of London. His research focuses on forward model learning methods and the analysis of prediction-based search agents in games with a special interest in partial-information games. He is active member of the IEEE in which he serves as the chair of the IEEE CIS Competitions Sub-Committee and member of the Games Technical Committee (GTC). Since 2017, he is organizing the Hearthstone AI competition to foster comparability of AI agents in card games.
Junge Zhang is now an associate professor of the University of Chinese Academy of Sciences. His major research interests include computer vision, pattern recognition, decision-making, deep reinforcement learning and multi-agent learning. In 2010 and 2011, he and his group members won the PASCAL VOC challenge on object detection and ranked second on object classification. In 2018, he and his team won the third-prize of the Starcraft AI challenge at the AIIDE Starcraft Competition. He has published over 50 papers including top-tier journals and conferences such as TPAMI, IJCV, TIP, CVPR, ICCV, NeurIPS, AAAI, IJCAI. He served as the Publicity Chair and the Technical Program Committee Member of several conferences, and the Peer reviewer of over 20 international journals and conferences and the member of IEEE CIS Games Technical Committee.
Chiara F. Sironi is a post-doctoral researcher at the Department of Data Science & Knowledge Engineering at Maastricht University, where she also received the Ph.D. degree in 2019. Her research focuses on on-line learning of search control for Monte-Carlo Tree Search (MCTS). She is using General Game Playing (GGP) as the main application domain and is also interested in applications to General Video Game Playing (GVGP). She participated in the organization of the 2018 IEEE Conference on Computational Intelligence and Games (CIG2018) as local chair and is currently a member of the Games Technical Committee (GTC) | IEEE Computational Intelligence Society.