Survey of 150+ Agent Memory Architectures: Self-Evolving Designs Boost Retention by 50%
blaizedsouza · x · 2026-08-12
A massive 90-page computer science survey maps over 150 agent memory architectures to build self-evolving long-horizon agents.
The paper introduces a 3D taxonomy, demonstrating that action-based memory and self-evolving structures boost long-horizon retention by 50%.
Crucially, the research argues that memory is no longer just a passive database lookup. It functions as an active operating system that trains models to execute tool actions, update parametric weights, and consolidate episodic traces into reusable skills.
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