A Modular Cognitive Model for Solving Complex Problems Based on "Memory Fragments"

Memory Fragments V2 introduces a modular memory architecture built on discrete knowledge fragments that activate conditionally. Version 2 adds the Appeal Trial—a sandbox workspace where the AI can fuse, modify, and reorganize fragments without altering the stable archive. Every proposed change requires explicit user approval; approved trials become new static fragments tracked in a directed acyclic graph of versions. The system leverages automatic metrics—token cost, functional coverage, hallucination risk—and maintains an audit trail to guarantee interpretability, token efficiency, and human governance of information