Abstract
This research aims to propose a theoretical model for the automatic balancing of games using the emotional state of the players. When launching a new game on the market, companies want to reach the largest number of people who are interested in playing the released title and for that they spend a large volume of resources to balance the games and deliver a good experience to the players. But this is not always possible because there are several types of players and each one has an expectation regarding the game. Some like a more difficult game, others prefer to just enjoy the narrative, but this, if defined statistically, limits the player to having multiple experiences, because the person may prefer to focus on the narrative and at the same time enjoy some moments with more action that, in a static configuration would be blocked. Given these assumptions, if the game can identify in real-time players’ emotions, it may be able to make changes to the game design, manipulating the narrative and elements of the gameplay. One way to increase the player’s involvement could be done through the monitoring of physiological signals and using AI algorithms to classify emotional states that potentiate changes in the scenarios and narrative of the story. In this study an approach based on biofeedback is explored, the measured physiological signals are used to make inferences about the emotional state of the player and this information is used to inform the game.
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Dworak, W., Filgueiras, E., Valente, J. (2020). Automatic Emotional Balancing in Game Design: Use of Emotional Response to Increase Player Immersion. In: Marcus, A., Rosenzweig, E. (eds) Design, User Experience, and Usability. Design for Contemporary Interactive Environments. HCII 2020. Lecture Notes in Computer Science(), vol 12201. Springer, Cham. https://doi.org/10.1007/978-3-030-49760-6_30
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