Federated Cognitive Memory: Tiered Access, Semiotic Density Scoring, and the First Federated Recall Benchmark

We present a federated cognitive memory architecture that combines Complementary Learning Systems (CLS) with a tiered access VIEW layer (L0-L3) and semiotic density scoring for multi-agent systems. The system enables agents to share memories through a governed bus (FCM) with membrane filtering, while maintaining economical wake-up costs (~200 tokens vs ~2K baseline). We introduce FederatedRecall, the first benchmark for measuring cross-agent memory retrieval quality. Experiments with 4 SYMBIONT-IMI synergies demonstrate that organism-level signals (channel weights, artifact approval, priority shifts) can inform memory tiering without replacing the underlying biological memory model. The L0-L3 hierarchy provides predictable context budgeting while the semiotic density scoring layer ensures high-value memories surface first during retrieval under token pressure.