Persistent Memory Infrastructure for Autonomous and Cooperative AI Systems

Abstract

Modern AI systems built on large language models demonstrate strong reasoning ability within a single interaction but lack durable, well-organized memory across interactions. Three deficiencies recur across current approaches: information that matters is lost once it leaves the active context; systems that do retain information accumulate it without bound, degrading retrieval quality through noise; and no widely deployed system gives multiple cooperating agents an efficient, consistent way to share what they have learned. This paper proposes AltMemory, a persistent memory infrastructure for autonomous and cooperative AI systems. AltMemory organizes agent memory into working, episodic, and semantic stores; introduces a Memory Ranking Engine and an Intelligent Forgetting Engine as explicit, first-class subsystems; and extends the architecture with Shared Memory Spaces for multi-agent cooperation. We describe the architecture, situate it against existing memory mechanisms (ChatGPT Memory, Claude Memory, MemGPT, LangChain Memory, and AutoGen), and propose a concrete experimental program covering semantic retrieval, forgetting, and shared-memory cooperation. We are explicit about the architecture’s current limitations: AltMemory is proposed and partially implemented (AltMemory v0.1), not yet validated at the scale or generality this paper describes