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Position Paper: Agent AI Towards a Holistic Intelligence

Authors :
Huang, Qiuyuan
Wake, Naoki
Sarkar, Bidipta
Durante, Zane
Gong, Ran
Taori, Rohan
Noda, Yusuke
Terzopoulos, Demetri
Kuno, Noboru
Famoti, Ade
Llorens, Ashley
Langford, John
Vo, Hoi
Fei-Fei, Li
Ikeuchi, Katsu
Gao, Jianfeng
Publication Year :
2024

Abstract

Recent advancements in large foundation models have remarkably enhanced our understanding of sensory information in open-world environments. In leveraging the power of foundation models, it is crucial for AI research to pivot away from excessive reductionism and toward an emphasis on systems that function as cohesive wholes. Specifically, we emphasize developing Agent AI -- an embodied system that integrates large foundation models into agent actions. The emerging field of Agent AI spans a wide range of existing embodied and agent-based multimodal interactions, including robotics, gaming, and healthcare systems, etc. In this paper, we propose a novel large action model to achieve embodied intelligent behavior, the Agent Foundation Model. On top of this idea, we discuss how agent AI exhibits remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. Furthermore, we discuss the potential of Agent AI from an interdisciplinary perspective, underscoring AI cognition and consciousness within scientific discourse. We believe that those discussions serve as a basis for future research directions and encourage broader societal engagement.<br />Comment: 22 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:2401.03568

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2403.00833
Document Type :
Working Paper