@article{Nogueira_Rodrigues_Oliveira_Nacke_2021, title={Guided Emotional State Regulation: Understanding and Shaping Players’ Affective Experiences in Digital Games}, volume={9}, url={https://ojs.aaai.org/index.php/AIIDE/article/view/12678}, DOI={10.1609/aiide.v9i1.12678}, abstractNote={ <p> Designing adaptive games for individual emotional experiences is a tricky task, especially when detecting a player’s emotional state in real time requires physiological sensing hardware and signal processing software. There is currently a lack of software that can identify and learn how emotional states in games are triggered. To address this problem, we developed a system capable of understanding the fundamental relations between emotional responses and their eliciting events. We propose time-evolving Affective Reaction Models (ARM), which learn new affective reactions and manage conflicting ones. These models are then meant to provide information on how a set of predetermined game parameters (e.g., enemy and item spawning, music and lighting effects) should be adapted, to modulate the player’s emotional state. In this paper, we propose and describe a framework for modulating player emotions and the main components involved in regulating players’ affective experience. We expect our technique will allow game designers to focus on defining high-level rules for generating gameplay experiences instead of having to create and test different content for each player type. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment}, author={Nogueira, Pedro and Rodrigues, Rui and Oliveira, Eugénio and Nacke, Lennart}, year={2021}, month={Jun.}, pages={51-57} }