用虚拟用户模拟加速AGI发展，解决交互数据与评估难题
The Indispensable Role of User Simulation in the Pursuit of AGI
- 构建能模仿人类行为的虚拟用户，生成真实交互数据
- 提升复杂AI系统的可扩展评估能力，支持自适应学习
- 适合研究AGI、人机交互与智能体训练的学者
迈向通用人工智能（AGI）面临重大瓶颈，尤其在评估复杂交互系统和获取大量交互数据方面。本文提出，用户模拟——即创建能够模仿人类与AI系统交互的计算代理——不仅是辅助工具，更是突破这些瓶颈的关键催化剂。真实可靠的模拟器可提供可扩展的评估环境，生成用于交互式学习的数据，并促进AGI核心所需的自适应能力。因此，用户模拟技术与智能任务代理的研究高度协同，必须并行推进。本文深入探讨用户模拟在AGI中的关键作用，分析构建真实模拟器的跨学科挑战，包括大语言模型带来的新问题，并提出未来研究方向。
原文摘要 · Abstract (English)
Progress toward Artificial General Intelligence (AGI) faces significant bottlenecks, particularly in rigorously evaluating complex interactive systems and acquiring the vast interaction data needed for training adaptive agents. This paper posits that user simulation -- creating computational agents that mimic human interaction with AI systems -- is not merely a useful tool, but is a critical catalyst required to overcome these bottlenecks and accelerate AGI development. We argue that realistic simulators provide the necessary environments for scalable evaluation, data generation for interactive learning, and fostering the adaptive capabilities central to AGI. Therefore, research into user simulation technology and intelligent task agents are deeply synergistic and must advance hand-in-hand. This article elaborates on the critical role of user simulation for AGI, explores the interdisciplinary nature of building realistic simulators, identifies key challenges including those posed by large language models, and proposes a future research agenda.
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