# A deep active inference model of the rubber-hand illusion

arXiv: https://arxiv.org/abs/2008.07408 · HTML: https://mlsanity.com/paper/2008.07408/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Aug 2020.

## Built on by (most cited first, 7 of 7)

- [Active Inference in Robotics and Artificial Agents: Survey and Challenges](https://mlsanity.com/paper/2112.01871/) (2021)
- [Multimodal VAE Active Inference Controller](https://mlsanity.com/paper/2103.04412/) (2021)
- [Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perception](https://mlsanity.com/paper/2105.04261/) (2021)
- [Deconstructing deep active inference](https://mlsanity.com/paper/2303.01618/) (2023)
- [Brain-inspired bodily self-perception model for robot rubber hand illusion](https://mlsanity.com/paper/2303.12259/) (2023)
- [Deep hybrid models: infer and plan in a dynamic world](https://mlsanity.com/paper/2402.10088/) (2024)
- [Dynamic planning in hierarchical active inference](https://mlsanity.com/paper/2402.11658/) (2024)

## Abstract (arXiv)

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.