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arXiv 2403.00833cs.AI
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立场论文:迈向整体智能的 Agent AI

Position Paper: Agent AI Towards a Holistic Intelligence

Stanford University(斯坦福大学);University of California, Los Angeles(加利福尼亚大学洛杉矶分校);Microsoft Gaming US(美国微软游戏部门);MSR Accelerator(微软研究院加速器);MSR AI Frontiers(微软研究院人工智能前沿部门);Microsoft Research Core(微软研究院核心部门);Microsoft Applied Robotics Research(微软应用机器人研究院)
Qiuyuan Huang, Naoki Wake, Bidipta Sarkar, Zane Durante, Ran Gong, Rohan Taori, Yusuke Noda, Demetri Terzopoulos, Noboru Kuno, Ade Famoti, Ashley Llorens, John … 展开作者

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

AI总结:

本文倡导从还原论转向整体智能,提出整合大型基础模型与智能体行动的 Agent AI 及 Agent Foundation Model,并探讨其跨领域能力与认知意识意义。

摘要:

大型基础模型的最新进展显著增强了我们对开放世界环境中感官信息的理解。在利用基础模型能力时,AI研究必须摆脱过度还原论,转而强调作为凝聚整体发挥作用的系统。具体而言,我们强调发展 Agent AI——一种将大型基础模型整合到智能体行动中的具身系统。Agent AI 这一新兴领域涵盖广泛的现有具身与基于智能体的多模态交互,包括机器人、游戏和医疗保健系统等。本文提出一种用于实现具身智能行为的新型大型行动模型,即 Agent Foundation Model。在这一思想之上,我们讨论 Agent AI 如何在多种领域和任务中展现卓越能力,挑战我们对学习与认知的理解。此外,我们从跨学科视角探讨 Agent AI 的潜力,在科学论述中强调 AI 认知与意识。我们相信这些讨论可为未来研究方向奠定基础,并鼓励更广泛的社会参与。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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