提出可自指的AGI架构EGO，模拟生物认知机制
EGO: a Recursive and Self-Referential Cognitive Architecture for Artificial General Intelligence
- 基于E语言构建自指系统，实现自我维持的智能结构
- 通过自组织机制突破大模型局限，支持认知演化
- 适合研究具身智能与通用人工智能的学者
人工通用智能（AGI）被视为自主自组织系统的涌现属性，基于自创生（autopoiesis）和具身认知原理，克服当前大语言模型（LLMs）的结构性缺陷。本文提出EGO（环境生成算子），一种基于形式化E语言的软件架构，具备自指性与内部组织维持能力，实现了马图拉纳（Maturana）提出的自创生理论，为人工智能与生物认知理论之间搭建桥梁。更多技术细节请参考arXiv上的技术文档。
原文摘要 · Abstract (English)
Artificial General Intelligence (AGI) is interpreted as an emergent property of autonomous and self-organizing systems, grounded in the principles of autopoiesis and embodied cognition, overcoming the structural limitations of current Large Language Models (LLMs). We introduce EGO (Environment Generative Operator), a software architecture based on the formal E-language, capable of self-referentiality and of maintaining its internal organization, thereby realizing Maturana's autopoiesis and providing a bridge between artificial intelligence and biological theories of cognition. For further details, please refer to the technical document on arXiv.
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