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Dream to Explore: 5-HT2a as Adaptive Temperature Parameter for Sophisticated Affective Inference

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Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1524))

Abstract

Relative to other neuromodulators, serotonin (5-HT) has received far less attention in machine learning and active inference. We will review prior work interpreting 5-HT1a signaling as an uncertainty parameter with opponency to dopamine. We will then discuss how 5-HT2a receptors may promote more exploratory policy selection by enhancing imaginative planning (as sophisticated affective inference). Finally, we will briefly comment on how qualitatively different effects may be observed across low and high levels of 5-HT2a signaling, where the latter may help agents to change self-adversarial policies and break free of maladaptive absorbing states in POMDPs.

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Acknowledgements

We gratefully acknowledge partial funding support from the Waterloo-Huawei Joint Innovation Lab within the project “the Active Inferential Meta-Learning Engine”.

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Authors and Affiliations

  1. Center for Psychedelic and Consciousness Research, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21224, USA

    Adam Safron

  2. David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada

    Zahra Sheikhbahaee

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  1. Adam Safron
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  1. IKIM, Ruhr-University Bochum, Bochum, Germany

    Michael Kamp

  2. University of Sydney, Sydney, NSW, Australia

    Irena Koprinska

  3. University of Namur, Namur, Belgium

    Adrien Bibal

  4. University of Rennes 1, Rennes, France

    Tassadit Bouadi

  5. University of Namur, Namur, Belgium

    Benoît Frénay

  6. Inria, Rennes, France

    Luis Galárraga

  7. University of Antwerp, Antwerp, Belgium

    José Oramas

  8. Ruhr University Bochum, Bochum, Germany

    Linara Adilova

  9. Royal Holloway University of London, Egham, UK

    Yamuna Krishnamurthy

  10. Ghent University, Ghent, Belgium

    Bo Kang

  11. Université Jean Monnet, Saint-Etienne cedex 2, France

    Christine Largeron

  12. Ghent University, Gent, Belgium

    Jefrey Lijffijt

  13. Telecom Paris, Paris, France

    Tiphaine Viard

  14. University of Bonn, Bonn, Germany

    Pascal Welke

  15. Norwegian Univesity of Science and Technology, Trondheim, Norway

    Massimiliano Ruocco

  16. BI Norwegian Business School, Oslo, Norway

    Erlend Aune

  17. University of Pisa, Pisa, Italy

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  44. UniCredit, Milan, Italy

    Valerio Bitetta

  45. UniCredit, Rome, Italy

    Ilaria Bordino

  46. UniCredit, Milan, Italy

    Andrea Ferretti

  47. Unicredit, Rome, Italy

    Francesco Gullo

  48. ENEA Headquarters, Portici, Italy

    Giovanni Ponti

  49. Unicredit, Rome, Italy

    Lorenzo Severini

  50. University of Porto, Porto, Portugal

    Rita Ribeiro

  51. University of Porto, Porto, Portugal

    João Gama

  52. UPC BarcelonaTech, Barcelona, Spain

    Ricard Gavaldà

  53. Northwestern University, Chicago, IL, USA

    Lee Cooper

  54. PD Personalised Healthcare, Basel, Switzerland

    Naghmeh Ghazaleh

  55. University of Lausanne, Lausanne, Switzerland

    Jonas Richiardi

  56. ETH Zurich, Basel, Switzerland

    Damian Roqueiro

  57. F. Hoffmann–La Roche Ltd, Basel, Switzerland

    Diego Saldana Miranda

  58. Novartis Pharma AG, Basel, Switzerland

    Konstantinos Sechidis

  59. University of Lisbon, Lisbon, Portugal

    Guilherme Graça

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Safron, A., Sheikhbahaee, Z. (2021). Dream to Explore: 5-HT2a as Adaptive Temperature Parameter for Sophisticated Affective Inference. In: Kamp, M., et al. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2021. Communications in Computer and Information Science, vol 1524. Springer, Cham. https://doi.org/10.1007/978-3-030-93736-2_56

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