A deep active inference model of the rubber-hand illusion
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
Cite
@article{arxiv.2008.07408,
title = {A deep active inference model of the rubber-hand illusion},
author = {Thomas Rood and Marcel van Gerven and Pablo Lanillos},
journal= {arXiv preprint arXiv:2008.07408},
year = {2020}
}
Comments
8 pages, 3 figures, Accepted in 1st International Workshop on Active Inference, in Conjunction with European Conference of Machine Learning 2020. The final authenticated publication is available online at https://doi.org/10.1007/978-3-030-64919-7_10