English

The Essential Role of Causality in Foundation World Models for Embodied AI

Artificial Intelligence 2024-05-01 v2 Computation and Language Machine Learning Robotics

Abstract

Recent advances in foundation models, especially in large multi-modal models and conversational agents, have ignited interest in the potential of generally capable embodied agents. Such agents will require the ability to perform new tasks in many different real-world environments. However, current foundation models fail to accurately model physical interactions and are therefore insufficient for Embodied AI. The study of causality lends itself to the construction of veridical world models, which are crucial for accurately predicting the outcomes of possible interactions. This paper focuses on the prospects of building foundation world models for the upcoming generation of embodied agents and presents a novel viewpoint on the significance of causality within these. We posit that integrating causal considerations is vital to facilitating meaningful physical interactions with the world. Finally, we demystify misconceptions about causality in this context and present our outlook for future research.

Keywords

Cite

@article{arxiv.2402.06665,
  title  = {The Essential Role of Causality in Foundation World Models for Embodied AI},
  author = {Tarun Gupta and Wenbo Gong and Chao Ma and Nick Pawlowski and Agrin Hilmkil and Meyer Scetbon and Marc Rigter and Ade Famoti and Ashley Juan Llorens and Jianfeng Gao and Stefan Bauer and Danica Kragic and Bernhard Schölkopf and Cheng Zhang},
  journal= {arXiv preprint arXiv:2402.06665},
  year   = {2024}
}