Games (GAME)

IEEE SSCI 2020 will run as a virtual conference.

Aim

Games are an ideal domain to study computational intelligence (CI) methods, as 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.

Scope

In general, papers are welcome that consider all kinds of methods (evolutionary computation, supervised learning, unsupervised learning, fuzzy systems, game-tree search, rolling horizon algorithms, MCTS, etc.) applied to games (card games, board games, mathematical games, action games, strategy games, role-playing games, arcade games, serious games, etc.). More information on this link.

Examples include but are not limited to:

• Adaptation in games
• Automatic game testing
• Coevolution in games
• Comparative studies (e.g.CI versus human-designed players)
• Dynamic difficulty in games
• Games as testbeds for algorithms
• Human player imitation
• Team AI
• Learning to play games
• Multi-agent and multi-strategy learning
• Player/opponent modelling
• Procedural content generation
• CI for serious games (e.g., games for health care, education or training)
• Results of game-based CI and open competitions
• Game AI for real-world decision making and planning

Symposium Chairs