Embodied AI in Machine Learning -- is it Really Embodied?

Fuente: arXiv
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Hauptverfasser: Hoffmann, Matej, Patni, Shubhan Parag
Format: Preprint
Veröffentlicht: 2025
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_version_ 1866909612093997056
author Hoffmann, Matej
Patni, Shubhan Parag
author_facet Hoffmann, Matej
Patni, Shubhan Parag
contents Embodied Artificial Intelligence (Embodied AI) is gaining momentum in the machine learning communities with the goal of leveraging current progress in AI (deep learning, transformers, large language and visual-language models) to empower robots. In this chapter we put this work in the context of "Good Old-Fashioned Artificial Intelligence" (GOFAI) (Haugeland, 1989) and the behavior-based or embodied alternatives (R. A. Brooks 1991; Pfeifer and Scheier 2001). We claim that the AI-powered robots are only weakly embodied and inherit some of the problems of GOFAI. Moreover, we review and critically discuss the possibility of cross-embodiment learning (Padalkar et al. 2024). We identify fundamental roadblocks and propose directions on how to make progress.
format Preprint
id arxiv_https___arxiv_org_abs_2505_10705
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Embodied AI in Machine Learning -- is it Really Embodied?
Hoffmann, Matej
Patni, Shubhan Parag
Artificial Intelligence
Neural and Evolutionary Computing
Robotics
68T40
I.2.9
Embodied Artificial Intelligence (Embodied AI) is gaining momentum in the machine learning communities with the goal of leveraging current progress in AI (deep learning, transformers, large language and visual-language models) to empower robots. In this chapter we put this work in the context of "Good Old-Fashioned Artificial Intelligence" (GOFAI) (Haugeland, 1989) and the behavior-based or embodied alternatives (R. A. Brooks 1991; Pfeifer and Scheier 2001). We claim that the AI-powered robots are only weakly embodied and inherit some of the problems of GOFAI. Moreover, we review and critically discuss the possibility of cross-embodiment learning (Padalkar et al. 2024). We identify fundamental roadblocks and propose directions on how to make progress.
title Embodied AI in Machine Learning -- is it Really Embodied?
topic Artificial Intelligence
Neural and Evolutionary Computing
Robotics
68T40
I.2.9
url https://arxiv.org/abs/2505.10705