Computational affective knowledge representation for agents located in a multicultural environment

In this paper, we propose a new computational model for affective knowledge representation that will be used for affective agents located in a multicultural environment. To this end, we present the results of two experiments, the first of which determines the most appropriate labels to define the pl...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Human-centric computing and information sciences 2024-05, Vol.14
Hauptverfasser: Taverner, Joaquin, Brännström, Andreas, Durães, Dalila, Vivancos, Emilio, Novais, Paulo, Nieves, Juan Carlos, Botti, Vicente
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In this paper, we propose a new computational model for affective knowledge representation that will be used for affective agents located in a multicultural environment. To this end, we present the results of two experiments, the first of which determines the most appropriate labels to define the pleasure-arousal dimensions in the culture and language of the agent's location. As an example, we use the Portuguese and Swedish languages. The second experiment identifies the most suitable values of pleasure-arousal dimensions for each emotion expressed in these example languages. The results obtained are compared with a previous model developed for agents interacting with European Spanish-speaking people. Results show significant differences in the values of pleasure and arousal associated with emotions across languages and cultures. The results also show no significant differences in gender or age when associating levels of pleasure-arousal to emotions. We propose two applications of these representation models, such as a model of an agent capable of adapting its affective behavior to different cultural environments and a human-aware planning scenario in which the agent uses this dimensional representation to recognize the user's affective state and select the best strategy to redirect that affective state to the target state.
ISSN:2192-1962
2192-1962
DOI:10.22967/HCIS.2024.14.030