Abstract
Research in neurobiology has provided evidence that emotions pervade human intelligence at many levels. However, “emotion” and “cognition” are still largely conceptualized as separate notions that “interact”, and untangling and modeling those interactions remains a challenge, both in biological and artificial systems. My research focuses on modeling in autonomous robots how “cognition”, “motivation” and “emotion” interact in what we could term embodied affective cognition, and particularly investigating how affect lies at the root of and drives how agents apprehend and interact with the world, making them “intelligent” in the sense of being able to adapt to their environments in flexible and beneficial ways. In this chapter, I discuss this issue as I illustrate how my embodied model of affect has been used in my group to ground a broad range of affective, cognitive and social skills such as adaptive action selection, different types of learning, development, and social interaction.
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Acknowledgements
The writing of this paper and the work reported here were carried out when I was a faculty member at the University of Hertfordshire. I am grateful to the past and present members of my group, the Embodied Emotion, Cognition and (Inter-)Action Lab, for their contributions to various aspects of the research discussed here, and to the organizers and participants of the “Emotional Machines” workshop for fruitful and insightful discussions. Funding for the research reported here was provided partly by the European Commission through grants HUMAINE (FP6-IST–507422), FEELIX GROWING (FP6-IST–045169), and ALIZ-E (FP7-ICT–248116), and partly by the University of Hertfordshire through various PhD studentships. The opinions expressed are solely the author’s.
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Cañamero, L. (2023). When Emotional Machines Are Intelligent Machines: Exploring the Tangled Knot of Affective Cognition with Robots. In: Misselhorn, C., Poljanšek, T., Störzinger, T., Klein, M. (eds) Emotional Machines. Technikzukünfte, Wissenschaft und Gesellschaft / Futures of Technology, Science and Society. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-37641-3_6
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