让智能体像人一样自主进化，动态适应环境变化。
Self-evolving Embodied AI
- 智能体能自更新记忆、自切换任务、自预测环境、自适应形态、自演化模型。
- 突破传统静态训练限制，在开放动态环境中实现持续适应与进化。
- 适合研究通用AI、自主机器人及复杂系统交互的学者参考。
具身人工智能（Embodied AI）是通过主动感知、具身认知和行动交互形成的智能系统。现有方法受限于人工设计的固定环境，智能体在预设记忆和任务中训练，仅能与相对静态的环境互动，难以应对真实世界中多变的形态和动态开放环境。本文提出自演化具身智能新范式，使智能体基于自身状态与环境变化，实现记忆自更新、任务自切换、环境自预测、形态自适应和模型自演化，旨在构建持续适应的自主进化智能。具体提出其定义、框架、组件与机制，系统综述已有实现技术，讨论实际应用并指明未来方向。我们认为，该范式使智能体能以类人方式自主学习与环境互动，为通用人工智能提供新视角。
原文摘要 · Abstract (English)
Embodied Artificial Intelligence (AI) is an intelligent system formed by agents and their environment through active perception, embodied cognition, and action interaction. Existing embodied AI remains confined to human-crafted setting, in which agents are trained on given memory and construct models for given tasks, enabling fixed embodiments to interact with relatively static environments. Such methods fail in in-the-wild setting characterized by variable embodiments and dynamic open environments. This paper introduces self-evolving embodied AI, a new paradigm in which agents operate based on their changing state and environment with memory self-updating, task self-switching, environment self-prediction, embodiment self-adaptation, and model self-evolution, aiming to achieve continually adaptive intelligence with autonomous evolution. Specifically, we present the definition, framework, components, and mechanisms of self-evolving embodied AI, systematically review state-of-the-art works for realized components, discuss practical applications, and point out future research directions. We believe that self-evolving embodied AI enables agents to autonomously learn and interact with environments in a human-like manner and provide a new perspective toward general artificial intelligence.
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