A deep active inference model of the rubber-hand illusion
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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.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Aug 2020.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 2; 2024: 2.
7 papers.
- 2021Active Inference in Robotics and Artificial Agents: Survey and Challengescited by 52
- 2021Multimodal VAE Active Inference Controllercited by 21
- 2021Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perceptioncited by 5
- 2023Deconstructing deep active inferencecited by 5
- 2023Brain-inspired bodily self-perception model for robot rubber hand illusioncited by 1
- 2024Deep hybrid models: infer and plan in a dynamic worldcited by 0
- 2024Dynamic planning in hierarchical active inferencecited by 0
- 2024Dynamic planning in hierarchical active inference18 Feb 2024
- 2024Deep hybrid models: infer and plan in a dynamic world1 Feb 2024
- 2023Brain-inspired bodily self-perception model for robot rubber hand illusion22 Mar 2023
- 2023Deconstructing deep active inference2 Mar 2023
- 2021Active Inference in Robotics and Artificial Agents: Survey and Challenges3 Dec 2021
- 2021Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perception10 May 2021
- 2021Multimodal VAE Active Inference Controller7 Mar 2021