Modelling Emotion Beyond Simulation: Algorithmic, Anthropological, and Political–Economic Approaches to Affect in Human–Robot Relations

Emotionally expressive machines have become central to debates in artificial intelligence, robotics, and social theory. Research in affective computing has formalised emotion algorithmically, while humanoid robotics has explored emotional expression through embodied interaction. These approaches, however, are often analysed in isolation and treated as politically neutral technical developments. This paper argues that emotion modelling constitutes a shared epistemic and political–economic practice spanning engineering, anthropology, and the organisation of affective labour under contemporary capitalism. Drawing on comparative analysis of affective computing research in the United Kingdom and humanoid robotics in Japan, the paper examines how emotion is operationalised through abstraction, performative validation, and normative constraint. It proposes a tripartite model of artificial emotion integrating affective dynamics, cognitive appraisal, and narrative–cultural mediation, and formally specifies this architecture using a dynamic state-space framework. By reframing artificial affect as the sedimentation of prior affective practices rather than emergent subjectivity, the paper clarifies the distinction between affect and emotion and provides a framework for analysing human–robot emotional interaction as a socio-technical and political phenomenon.

Emotion Modelling, Affective Computing, Dynamic State-Space Models

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