A4 Artikkeli konferenssijulkaisussa
Simulating Emotions With an Integrated Computational Model of Appraisal and Reinforcement Learning (2024)

Zhang, J. E., Hilpert, B., Broekens, J., & Jokinen, J. P.P. (2024). Simulating Emotions With an Integrated Computational Model of Appraisal and Reinforcement Learning. In F. F. Mueller, P. Kyburz, J. R. Williamson, C. Sas, M. L. Wilson, P. T. Dugas, & I. Shklovski (Eds.), CHI '24 : Proceedings of the CHI Conference on Human Factors in Computing Systems (Article 703). ACM. https://doi.org/10.1145/3613904.3641908

JYU-tekijät tai -toimittajat

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Zhang, Jiayi Eurus; Hilpert, Bernhard; Broekens, Joost; Jokinen, Jussi P. P.

Emojulkaisu: CHI '24 : Proceedings of the CHI Conference on Human Factors in Computing Systems

Emojulkaisun toimittajat: Mueller, Florian Floyd; Kyburz, Penny; Williamson, Julie R.; Sas, Corina; Wilson, Max L.; Dugas, Phoebe Toups; Shklovski, Irina

Konferenssi:

Konferenssin paikka ja aika: Honolulu, USA, 11.-16.5.2024

eISBN: 979-8-4007-0330-0

Julkaisuvuosi: 2024

Ilmestymispäivä: 11.05.2024

Artikkelinumero: 703

Kustantaja: ACM

Julkaisumaa: Yhdysvallat (USA)

Julkaisun kieli: englanti

DOI: https://doi.org/10.1145/3613904.3641908

Julkaisun avoin saatavuus: Avoimesti saatavilla

Julkaisukanavan avoin saatavuus: Osittain avoin julkaisukanava

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/94912

Tiivistelmä

Predicting users’ emotional states during interaction is a long-standing goal of affective computing. However, traditional methods based on sensory data alone fall short due to the interplay between users’ latent cognitive states and emotional responses. To address this, we introduce a computational cognitive model that simulates emotion as a continuous process, rather than a static state, during interactive episodes. This model integrates cognitive-emotional appraisal mechanisms with computational rationality, utilizing value predictions from reinforcement learning. Experiments with human participants demonstrate the model’s ability to predict and explain the emergence of emotions such as happiness, boredom, and irritation during interactions. Our approach opens the possibility of designing interactive systems that adapt to users’ emotional states, thereby improving user experience and engagement. This work also deepens our understanding of the potential of modeling the relationship between reward processing, reinforcement learning, goal-directed behavior, and appraisal.

YSO-asiasanat: simulointi; mallintaminen; kognitiiviset prosessit; laskennallinen tiede; koneoppiminen; vahvistusoppiminen; tunteet; palkitseminen; arvostelu (toiminta)

Liittyvät organisaatiot

OKM-raportointi: Kyllä

Alustava JUFO-taso: 3