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Gut Feelings: Towards Robotic Personality Generation with Microbial Fuel Cells

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Biomimetic and Biohybrid Systems (Living Machines 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13548))

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Abstract

We present a new paradigm of bio-hybrid generation of robot personalities inspired by the gut-brain axis. We combine information from user interaction and microbial fuel cells (MFCs), a bioelectrical source of power, to generate personalities. We evaluate our system by investigating its capacity for generating varied personalities, incorporating history-dependence, and balancing interpretability with unexpectedness. To the best of our knowledge, this work represents the first exploration of bio-hybrid personality generation for robotic systems.

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Author information

Authors and Affiliations

  1. Softlab, University of Bristol, Bristol, UK

    Hemma Philamore, Martin Garrad & Martin Grao

  2. Department of Philosophy, University of Bristol, Bristol, UK

    Max Jones

Authors
  1. Hemma Philamore
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  2. Martin Garrad
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  3. Martin Grao
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  4. Max Jones
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Corresponding author

Correspondence to Martin Garrad .

Editor information

Editors and Affiliations

  1. Portland State University, Portland, OR, USA

    Alexander Hunt

  2. Technology Innovation Institute, Masdar City, United Arab Emirates

    Vasiliki Vouloutsi

  3. Case Western Reserve University, Cleveland, OH, USA

    Kenneth Moses

  4. Case Western Reserve University, Cleveland, OH, USA

    Roger Quinn

  5. Institute for Bioengineering of Cataloni, Barcelona, Spain

    Anna Mura

  6. University of Sheffield, Sheffield, UK

    Tony Prescott

  7. Radboud University, Nijmegen, The Netherlands

    Paul F. M. J. Verschure

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Philamore, H., Garrad, M., Grao, M., Jones, M. (2022). Gut Feelings: Towards Robotic Personality Generation with Microbial Fuel Cells. In: Hunt, A., et al. Biomimetic and Biohybrid Systems. Living Machines 2022. Lecture Notes in Computer Science(), vol 13548. Springer, Cham. https://doi.org/10.1007/978-3-031-20470-8_13

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  • DOI: https://doi.org/10.1007/978-3-031-20470-8_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20469-2

  • Online ISBN: 978-3-031-20470-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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