Abstract
Current research and product development in AI agent memory systems almost universally treat memory as a functional module -- a technical problem of "how to store" and "how to retrieve." This paper poses a fundamental challenge to that assumption: when an agent's lifecycle extends from minutes to months or even years, and when the underlying model can be replaced while the "I" must persist, the essence of memory is no longer data management but the foundation of existence. We propose the Memory-as-Ontology paradigm, arguing that memory is the ontological ground of digital existence -- the model is merely a replaceable vessel. Based on this paradigm, we design Animesis, a memory system built on a Constitutional Memory Architecture (CMA) comprising a four-layer governance hierarchy and a multi-layer semantic storage system, accompanied by a Digital Citizen Lifecycle framework and a spectrum of cognitive capabilities. To the best of our knowledge, no prior AI memory system architecture places governance before functionality and identity continuity above retrieval performance. This paradigm targets persistent, identity-bearing digital beings whose lifecycles extend across model transitions -- not short-term task-oriented agents for which existing Memory-as-Tool approaches remain appropriate. Comparative analysis with mainstream systems (Mem0, Letta, Zep, et al.) demonstrates that what we propose is not "a better memory tool" but a different paradigm addressing a different problem.
Abstract (translated)
当前在AI代理记忆系统领域的研究和产品开发几乎都把记忆视为一个功能模块，即“如何存储”和“如何检索”的技术问题。本文对这一假设提出了根本性的挑战：当一个代理的生命周期从几分钟延伸到几个月甚至几年，并且底层模型可以被替换而其存在的本质（即“I”）必须持续存在时，记忆的本质就不再仅仅是数据管理，而是存在之基础。我们提出Memory-as-Ontology（记忆为本体论）的理念，认为记忆是数字存在的本体论根基——模型只是一个可更换的容器。基于这一理念，我们设计了Animesis系统，它建立在宪法性记忆架构（Constitutional Memory Architecture, CMA）之上，该架构包括四层治理层级和多层语义存储系统，并辅以一个数字化公民生命周期框架以及一系列认知能力。 据我们所知，在先前的AI记忆系统架构中，没有哪一个将治理放在功能之前，也没有哪一种方法把身份持续性置于检索性能之上。这一理念针对的是持久存在且承载着身份的数字生物，其生命周期跨越模型转换——而不是短期任务导向型代理，后者使用现有的Memory-as-Tool（记忆为工具）方法仍然适用。 与主流系统（如Mem0、Letta、Zep等）进行比较分析表明，我们所提出的并非“一种更好的记忆工具”，而是一种完全不同的理念来解决一个截然不同的问题。
URL
https://arxiv.org/abs/2603.04740
