Special Sessions

Real-time strategy games (RTS) are an active area of research as well as a popular branch of industrial game production, with high commercial interest. Although player satisfaction is the ultimate goal also for these games, they are usually too complex to come up with human-level AI that is not cheating. In consequence, for RTS games it is as desirable to play well as it is to make the game interesting. Also, RTS games have many aspects that call for CI or other innovative methods, as strategy, tactics, resource management, and many more. The task of the special session is to advance the state of research on RTS by new methods or new applications of methods, new concepts, and also the analysis of existing methods or problems.

Modern computer games provide an ideal environment for the study of human behavior. Being closed worlds of considerable complexity, games allow for investigating behavior patterns, decision making, and preference modeling. Advances in these areas will improve game design and game play and have a high potential as enablers of future businesses. This requires mechanisms for recording and storage of large amounts of in-game data as well as efficient methods for the processing and analysis of large scale data sets.

Organized by the IEEE CIS Task Force on Player Satisfaction Modeling and the Humaine Association SIG on Games and Entertainment.

Analyzing, capturing and synthesizing player experience in both traditional screen-based games and augmented- and mixed-reality platforms has been a challenging area within the crossroads of cognitive science, psychology, artificial intelligence and human-computer interaction.

New gameplay modalities enhance the importance of the study and the complexity of player experience. Artificial and computational intelligence can be used to synthesize the affective state of player (and non-player) characters, based on multiple modalities of player-game interaction. Multiple modalities of input can also provide a novel means for game platforms to measure player satisfaction and engagement when playing, without necessarily having to resort to post-play and off-line questionnaires. For instance, players immersed by gameplay will rarely gaze away from the screen, while disappointed or indifferent players will typically show very little response or emotion. AI/CI algorithms can also be used to adapt the game to maximize player’s experience, thereby, closing the affective game loop: e.g. change the game soundtrack to a vivid or dimmer tune to match the player’s powerful stance or prospect of defeat; maximize frustration by increasing the number of gaps in a platform game. From the point of view of non-player characters, an injured or frustrated opponent will look down when facing defeat, informing the users about its status, much in the way a human opponent would be expected to.

This special session aims at bringing together specialists from computational intelligence, affective computing, and multi-modal interfaces to discuss advances in player experience and affect induction, sensing and modeling.

Modern racing games provide vivid representations of the game environment and very realistic physics engines that accurately model the dynamics of racing cars. At the same time, they also need a very sophisticated and believable AI to meet the increasingly high expectations of players.Computational intelligence offers a range of interesting new ideas and techniques for racing game developers. So far, both published academic research, the entrants of the recurring simulated car racing competitions, and some notable applications in high-end commercial games have shown that computational intelligence techniques can successfully be used in the racing games domain.

The aim of this special session is to bring together leading researchers in this field and gather the best new research, the most innovative ideas, and the future directions within this research area.