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A Deep Active Inference Model of the Rubber-Hand Illusion

  • Thomas RoodEmail author
  • Marcel van Gerven
  • Pablo Lanillos
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1326)

Abstract

Understanding how perception and action deal with sensorimotor conflicts, such as the rubber-hand illusion (RHI), is essential to understand how the body adapts to uncertain situations. Recent results in humans have shown that the RHI not only produces a change in the perceived arm location, but also causes involuntary forces. Here, we describe a deep active inference agent in a virtual environment, which we subjected to the RHI, that is able to account for these results. We show that our model, which deals with visual high-dimensional inputs, produces similar perceptual and force patterns to those found in humans.

Keywords

Active inference Rubber-hand Illusion Free-energy optimization Deep learning 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Thomas Rood
    • 1
    Email author
  • Marcel van Gerven
    • 1
  • Pablo Lanillos
    • 1
  1. 1.Department of Artificial IntelligenceDonders Institute for Brain, Cognition and BehaviourNijmegenThe Netherlands

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