Position Paper: Agent AI Towards a Holistic Intelligence
On the map: LLM agents and tool use → Multimodal and embodied agents
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 68 of its 152 references that are in the map. First posted on arXiv 28 Feb 2024.
Builds on
68 of 152 references.
Closest ancestors · 4
Same direction, newest first
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- 2023Can an Embodied Agent Find Your "Cat-shaped Mug"? LLM-Guided Exploration for Zero-Shot Object Navigation6 Mar
Other references · 64
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- 2016Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotationscited by 2,646
- 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,302
- 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
- 2023PaLM-E: An Embodied Multimodal Language Modelcited by 2,037
- 2022RT-1: Robotics Transformer for Real-World Control at Scalecited by 2,007
- 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
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- 2023VideoChat: Chat-Centric Video Understandingcited by 851
- 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 850
- 2021Retrieval Augmentation Reduces Hallucination in Conversationcited by 691
- 2018Object Hallucination in Image Captioningcited by 661
- 2023Eureka: Human-Level Reward Design via Coding Large Language Modelscited by 542
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- 2023Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agentscited by 396
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