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2020 Fiscal Year Annual Research Report

動的かつ不確実な環境下での適応的知覚と行動に関する研究

Research Project

Project/Area Number 19F19809
Research InstitutionInstitute of Physical and Chemical Research

Principal Investigator

豊泉 太郎  国立研究開発法人理化学研究所, 脳神経科学研究センター, チームリーダー (50547461)

Co-Investigator(Kenkyū-buntansha) BALTIERI MANUEL  国立研究開発法人理化学研究所, 脳神経科学研究セン ター, 外国人特別研究員
Project Period (FY) 2019-11-08 – 2022-03-31
Keywordsuncertainty / bayesian inference / closed-loop control
Outline of Annual Research Achievements

This project tackles the ongoing need for better computational models that can describe more naturalistic behaviour in humans and other agents alike. Via the inclusion of more realistic accounts of uncertainty in closed-loop environments, we propose an interdisciplinary approach to the study of perceptual and motor processes in naturalistic conditions. This approach will integrate computational models including accounts of unpredictable variations in the world and novel experiments focused on dynamic environments.

To achieve the aforementioned goal, I spent some months reviewing the literature to better assess the state of current modelling approaches to perceptual decision making, including for example theories of predictive coding, control theory and variational free energy minimisation. After doing so, I wrote and submitted different papers explaining some of the limitations of a number of current proposals.

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

The literature review already produced some published works, and more technical manuscripts are in the working.

Strategy for Future Research Activity

In the upcoming months, I will continue working on current manuscripts in order to enable a better understanding of the mathematical toolkits necessary to pursue modelling of more realistic experimental setups and their consequences. This will entail establishing clearer and more direct connections to other existing frameworks, with a focus on control theoretic frameworks applied to sensorimotor control.

The outcomes of these projects will be theoretical manuscripts with technical details highlighting different assumptions and situations under which new frameworks ought to be developed, with the goal of modelling of human behaviour and perceptual decision making.

  • Research Products

    (6 results)

All 2021 2020

All Journal Article (4 results) (of which Int'l Joint Research: 3 results,  Peer Reviewed: 4 results,  Open Access: 1 results) Presentation (2 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] Embodied skillful performance: where the action is2021

    • Author(s)
      Hipolito Ines、Baltieri Manuel、Friston Karl、Ramstead Maxwell J. D.
    • Journal Title

      Synthese

      Volume: 199 Pages: 4457~4481

    • DOI

      10.1007/s11229-020-02986-5

    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Predictions in the eye of the beholder: an active inference account of Watt governors2020

    • Author(s)
      Baltieri Manuel、Buckley Christopher L.、Bruineberg Jelle
    • Journal Title

      Artificial Life Conference Proceedings

      Volume: - Pages: 121-129

    • DOI

      10.1162/isal_a_00288

    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] A Bayesian perspective on classical control2020

    • Author(s)
      Baltieri Manuel
    • Journal Title

      2020 International Joint Conference on Neural Networks (IJCNN)

      Volume: - Pages: -

    • DOI

      10.1109/IJCNN48605.2020.9206617

    • Peer Reviewed
  • [Journal Article] Scaling Active Inference2020

    • Author(s)
      Tschantz Alexander、Baltieri Manuel、Seth Anil. K.、Buckley Christopher L.
    • Journal Title

      2020 International Joint Conference on Neural Networks (IJCNN)

      Volume: - Pages: -

    • DOI

      10.1109/IJCNN48605.2020.9207382

    • Peer Reviewed / Int'l Joint Research
  • [Presentation] Predictions in the eye of the beholder: an active inference account of Watt governors.2020

    • Author(s)
      Manuel Baltieri
    • Organizer
      ALife 2020
    • Int'l Joint Research
  • [Presentation] A Bayesian perspective on classical control2020

    • Author(s)
      Manuel Baltieri
    • Organizer
      IJCNN 2020
    • Int'l Joint Research

URL: 

Published: 2021-12-27  

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