Exploring extensions of neurotransmitter-based emotion models
Advancements in artificial intelligence have significantly enhanced the gaming experience, enabling more engaging and adaptive interactions between players and digital characters. A key aspect of this progress is the ability of non-player characters (NPCs) to display more lifelike realistic emotion...
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| Format: | Article |
| Language: | English |
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Brazilian Computer Society
2025-06-01
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| Series: | Journal on Interactive Systems |
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| Online Access: | https://journals-sol.sbc.org.br/index.php/jis/article/view/5642 |
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| author | João Ricardo Pinheiro Paulo de Tarso Fernandes Augusto Baffa Bruno Feijó |
| author_facet | João Ricardo Pinheiro Paulo de Tarso Fernandes Augusto Baffa Bruno Feijó |
| author_sort | João Ricardo Pinheiro |
| collection | DOAJ |
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Advancements in artificial intelligence have significantly enhanced the gaming experience, enabling more engaging and adaptive interactions between players and digital characters. A key aspect of this progress is the ability of non-player characters (NPCs) to display more lifelike realistic emotional responses that simulate the fluid and unpredictable nature of human emotions. This work presents a novel emotion model integrating Lövheim’s Cube of Emotions with Plutchik’s Wheel of Emotions, combining the dynamic aspects of the former with the detailed structure of the latter. The model was expanded from a 22-emotion, 21-point mapping to a more detailed version with 24 emotions across 52 points, allowing for better emotional differentiation. Two algorithms were upgraded and tested: an extended cube of emotions using the Euclidean distance, and the same cube incorporating fuzzy logic. Both methods showed significantly better results than their previous versions, with the Euclidean being the best overall. That indicates a more precise mapping of emotions. However, it can only return one emotion at a time. While the Fuzzy Logic method allows for more than one emotional response at the same time, associating neurotransmitters and emotions within fuzzy rules was quite complex.
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| format | Article |
| id | doaj-art-89fec2d1ef5c44eb95b513feeeb00e29 |
| institution | DOAJ |
| issn | 2763-7719 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Brazilian Computer Society |
| record_format | Article |
| series | Journal on Interactive Systems |
| spelling | doaj-art-89fec2d1ef5c44eb95b513feeeb00e292025-08-20T03:22:57ZengBrazilian Computer SocietyJournal on Interactive Systems2763-77192025-06-0116110.5753/jis.2025.5642Exploring extensions of neurotransmitter-based emotion modelsJoão Ricardo Pinheiro0Paulo de Tarso Fernandes1Augusto Baffa2Bruno Feijó3Pontifical Catholic University of Rio de JaneiroPontifical Catholic University of Rio de JaneiroPontifical Catholic University of Rio de JaneiroPontifical Catholic University of Rio de Janeiro Advancements in artificial intelligence have significantly enhanced the gaming experience, enabling more engaging and adaptive interactions between players and digital characters. A key aspect of this progress is the ability of non-player characters (NPCs) to display more lifelike realistic emotional responses that simulate the fluid and unpredictable nature of human emotions. This work presents a novel emotion model integrating Lövheim’s Cube of Emotions with Plutchik’s Wheel of Emotions, combining the dynamic aspects of the former with the detailed structure of the latter. The model was expanded from a 22-emotion, 21-point mapping to a more detailed version with 24 emotions across 52 points, allowing for better emotional differentiation. Two algorithms were upgraded and tested: an extended cube of emotions using the Euclidean distance, and the same cube incorporating fuzzy logic. Both methods showed significantly better results than their previous versions, with the Euclidean being the best overall. That indicates a more precise mapping of emotions. However, it can only return one emotion at a time. While the Fuzzy Logic method allows for more than one emotional response at the same time, associating neurotransmitters and emotions within fuzzy rules was quite complex. https://journals-sol.sbc.org.br/index.php/jis/article/view/5642Emotion ModelingLövheim CubePlutchik’s WheelFuzzy LogicNeuroscience-inspired AIDynamic Emotional Responses |
| spellingShingle | João Ricardo Pinheiro Paulo de Tarso Fernandes Augusto Baffa Bruno Feijó Exploring extensions of neurotransmitter-based emotion models Journal on Interactive Systems Emotion Modeling Lövheim Cube Plutchik’s Wheel Fuzzy Logic Neuroscience-inspired AI Dynamic Emotional Responses |
| title | Exploring extensions of neurotransmitter-based emotion models |
| title_full | Exploring extensions of neurotransmitter-based emotion models |
| title_fullStr | Exploring extensions of neurotransmitter-based emotion models |
| title_full_unstemmed | Exploring extensions of neurotransmitter-based emotion models |
| title_short | Exploring extensions of neurotransmitter-based emotion models |
| title_sort | exploring extensions of neurotransmitter based emotion models |
| topic | Emotion Modeling Lövheim Cube Plutchik’s Wheel Fuzzy Logic Neuroscience-inspired AI Dynamic Emotional Responses |
| url | https://journals-sol.sbc.org.br/index.php/jis/article/view/5642 |
| work_keys_str_mv | AT joaoricardopinheiro exploringextensionsofneurotransmitterbasedemotionmodels AT paulodetarsofernandes exploringextensionsofneurotransmitterbasedemotionmodels AT augustobaffa exploringextensionsofneurotransmitterbasedemotionmodels AT brunofeijo exploringextensionsofneurotransmitterbasedemotionmodels |