The Emotional State Transition Model Empowered by Genetic Hybridization Technology on Human–Robot Interaction

Abstract

In the rapidly developing field of Human-Robot Interaction (HRI), simulating human emotional states poses significant challenges due to the inherent complexity and unpredictability of human emotions. Addressing the limitations in artificial emotion simulation, such as fuzzy theory, memory mechanism, and etc., we explore the genetic canvas that portrays emotions as an interplay of myriad complex expressions. By simulating emotional states using Genetic Hybridization Technology (GHT) in the Emotional State Transition (EST) model, this study investigates the role of genetics in artificial emotion simulation, outlines the creation of EST morphological genes, and validates their consistency. The results indicate that the Fréchet distance for EST curves ranges between 0.072 and 0.239, suggesting a high level of consistency between the experimentally generated EST curves and the newly generated EST morphological genes. This finding demonstrates the effectiveness of our proposed method and supports its future use in experimental design under various conditions. Additionally, we identified instances of gene mutations that occurred during the gene hybridization process, as highlighted in the results for EST curve (h). Despite this variation, the Fréchet distance remains within a reasonable range, further validating the reliability of our methodology. This study establishes a precedent for the methodology of emotional simulation, providing new research pathways for enriching HRI, through substantive exploration of the relationship between Artificial emotional intelligence (AEI) and GHT.

Keywords

• Emotional state transition model
• genetic hybridization technology
• human-robot interaction
• artificial emotional intelligence