标题： AI代理和代理式AI——为未来制造导航众多概念 显示英文标题

标题： AI Agents and Agentic AI-Navigating a Plethora of Concepts for Future Manufacturing

摘要： 人工智能代理是设计用于在动态环境中感知、推理和行动的自主系统。 随着生成式人工智能（GenAI）的快速发展，大型语言模型（LLMs）和多模态大型语言模型（MLLMs）显著提升了人工智能代理在语义理解、复杂推理和自主决策方面的能力。 同时，代理式人工智能的兴起突显了在动态和复杂环境中适应性和目标导向的自主性。 基于大型语言模型的人工智能代理（LLM-Agents）、基于多模态大型语言模型的人工智能代理（MLLM-Agents）以及代理式人工智能，有助于扩展人工智能在信息处理、环境感知和自主决策方面的能力，为智能制造开辟了新的途径。 然而，这些新兴人工智能范式在智能制造中的定义、能力边界和实际应用仍不明确。 为解决这一差距，本研究系统地回顾了人工智能和人工智能代理技术的发展历程，探讨了LLM-Agents、MLLM-Agents和代理式人工智能的核心概念和技术进展，并探索了它们在制造领域的潜在应用及其整合，以及可能面临的挑战。 显示英文摘要

摘要： AI agents are autonomous systems designed to perceive, reason, and act within dynamic environments. With the rapid advancements in generative AI (GenAI), large language models (LLMs) and multimodal large language models (MLLMs) have significantly improved AI agents' capabilities in semantic comprehension, complex reasoning, and autonomous decision-making. At the same time, the rise of Agentic AI highlights adaptability and goal-directed autonomy in dynamic and complex environments. LLMs-based AI Agents (LLM-Agents), MLLMs-based AI Agents (MLLM-Agents), and Agentic AI contribute to expanding AI's capabilities in information processing, environmental perception, and autonomous decision-making, opening new avenues for smart manufacturing. However, the definitions, capability boundaries, and practical applications of these emerging AI paradigms in smart manufacturing remain unclear. To address this gap, this study systematically reviews the evolution of AI and AI agent technologies, examines the core concepts and technological advancements of LLM-Agents, MLLM-Agents, and Agentic AI, and explores their potential applications in and integration into manufacturing, along with the potential challenges they may face.