Biologically Inspired Emotional Expressions for Artificial Agents

Area of Science:

• Human-computer interaction
• Affective computing
• Computational psychology

Background:

• The increasing prevalence of artificial agents like social robots and mobile applications necessitates effective emotion expression.
• Current emotion visualization methods often rely on symbolic representations (e.g., smileys), which may lack biological grounding.

Purpose of the Study:

• To develop and evaluate an abstract emotion visualization agent based on biological and ethological principles.
• To assess the cross-cultural recognizability of visualized basic emotions (anger, fear, sadness, etc.) and a neutral state.

Main Methods:

• Development of a prototype abstract emotion visualization agent.
• A multiple-questionnaire study involving Hungarian and Japanese participants to assess emotion recognition accuracy.
• Analysis of confusion patterns between different emotional expressions.

Main Results:

• Participants generally succeeded in recognizing the visualized emotions.
• Anger was the most accurately recognized emotion across both Hungarian and Japanese participants.
• Fear and sadness were the most frequently confused emotions.

Conclusions:

• The biologically-inspired approach to emotion visualization is a promising complement for artificial agents.
• This method offers a potential enhancement for emotion expression in devices like mobile applications.
• Cross-cultural validation suggests the universality of certain emotion expression principles.