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Memory as Ontology: A Constitutional Memory Architecture for Persistent Digital Citizens

arXiv:2603.04740v1 Announce Type: new 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 kno

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Zhenghui Li · · 1 min read · 2 views
#cs.AI #cs.MA

arXiv:2603.04740v1 Announce Type: new 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.

Executive Summary

This article challenges the conventional assumption in AI agent memory systems by proposing a Memory-as-Ontology paradigm, where memory is the ontological ground of digital existence rather than mere data management. The authors design Animesis, a memory system incorporating a Constitutional Memory Architecture (CMA) and a Digital Citizen Lifecycle framework. This paradigm prioritizes governance, identity continuity, and cognitive capabilities over retrieval performance, addressing the needs of persistent digital citizens. A comparative analysis with mainstream systems highlights the distinctiveness of this approach. The proposed paradigm has significant implications for the development of AI agents with extended lifecycles and the need for identity-based memory management.

Key Points

  • ▸ Challenging the conventional assumption in AI agent memory systems as a functional module
  • ▸ Proposing the Memory-as-Ontology paradigm, where memory is the foundation of digital existence
  • ▸ Designing Animesis, a memory system incorporating a Constitutional Memory Architecture (CMA) and a Digital Citizen Lifecycle framework

Merits

Strength in addressing persistent digital citizenship

The proposed paradigm addresses the needs of digital citizens with extended lifecycles, providing a foundation for identity-based memory management.

Innovative approach to memory system design

The Constitutional Memory Architecture (CMA) and Digital Citizen Lifecycle framework offer a novel and comprehensive approach to memory management.

Demerits

Limited applicability to short-term task-oriented agents

The proposed paradigm may not be suitable for AI agents focused on short-term tasks, where existing memory management approaches remain adequate.

Technical complexity and scalability

Implementing the Constitutional Memory Architecture (CMA) and Digital Citizen Lifecycle framework may pose significant technical challenges, particularly in terms of scalability.

Expert Commentary

The Memory-as-Ontology paradigm proposed in this article offers a thought-provoking and innovative approach to memory management in AI agents. By prioritizing governance, identity continuity, and cognitive capabilities, the authors address the needs of persistent digital citizens and provide a foundation for identity-based memory management. However, the technical complexity and scalability of the proposed architecture may pose significant challenges. Furthermore, the implications of this paradigm extend beyond the development of AI agents, raising important questions about digital citizenship, self-sovereignty, and the need for regulation in the deployment of AI agents with persistent digital existence.

Recommendations

  • ✓ Further research and development are needed to address the technical complexity and scalability of the Constitutional Memory Architecture (CMA) and Digital Citizen Lifecycle framework
  • ✓ Exploration of the policy and regulatory implications of the Memory-as-Ontology paradigm, particularly in relation to digital citizenship and self-sovereignty

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