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Prototyping an Architecture of Affective Robotic Systems Based on the Theory of Constructed Emotion

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Social Robotics (ICSR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13817))

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Abstract

Recognizing emotions is one of the most difficult tasks for computers. Most emotion theories claim that basic emotions are genetically endowed, whereas the theory of constructed emotion states that our brain constantly uses past experiences to guide our actions and construct emotions and generates in each situation a new instance of emotion. This allows us to describe emotions in terms of multidimensional values – valence, arousal, and dominance. By describing emotion instances in terms of these dimensions, we can start comparing different emotional states based on the user input and reflect by a computational system on the emotional state of the user. This paper describes the design, implementation, and validation of a chatbot that can recognize the emotions of its human user and generates replies based on the current emotional state of the user perceived by it. The purpose of the chatbot is to prototype an emotion-aware social robot, which is based on the theory of constructed emotion.

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Acknowledgements

The research work reported in this article has received funding from the Pilots for Healthy and Active Ageing (Pharaon) project of the European Union’s Horizon 2020 research and innovation programme under the grant agreement no. 857188 and from the European Social Fund via the IT Academy programme. The authors are expressing their gratitude to Syazwanie Filzah Zulkifli for her hard work in formatting the final version of this paper.

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Correspondence to Kuldar Taveter .

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Taveter, K., Kirikal, A. (2022). Prototyping an Architecture of Affective Robotic Systems Based on the Theory of Constructed Emotion. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13817. Springer, Cham. https://doi.org/10.1007/978-3-031-24667-8_49

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  • DOI: https://doi.org/10.1007/978-3-031-24667-8_49

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