World Representation
How memory is structured as a navigable world — graphs, hypergraphs, and representations that scale.
11 articles
Agent Memory Deduplication: The Missing Error Rate
Six agent-memory systems, read at pinned commits: hardcoded similarity thresholds, no published error rate, and no way to undo a merge.
Is Memory Hyperbolic? What Neuroscience Shows
Is memory hyperbolic? Cognitive maps are real, but one narrow CA1 result and indirect odor evidence do not establish a universal memory geometry.
The Independence Illusion: When AI Agents Agree
AI agent consensus can be weak evidence when agents share models, sources, prompts, or memory. Count independent provenance chains instead.
Who Wins When Agents Disagree? The Authority Problem
When voting, reputation, and consensus can fail for multi-agent memory — and the published alternatives: outcomes, meta-knowledge, independence, reasons.
Bitemporal Memory for AI Agents: The Missing Axis
Bitemporal memory tracks valid time and transaction time — settled engineering. One reviewed agent system ships it; none of seven benchmarks tests it.
Provenance in Agent Memory: The Missing Who
Provenance in agent memory is who asserted a fact, on what evidence, by what derivation. Timestamps keep the when and drop the who — what to record instead.
Graph Memory MCP Servers: What Agents Actually Get
Graph memory MCP comparison of Graphiti, Cognee, Neo4j, and server-memory across traversal, temporal support, provenance, and STOP gaps.
The GraphRAG Tax: When a Knowledge Graph Doesn't Pay
GraphRAG vs RAG decision guide: when a knowledge graph's build, query, and latency cost pays off for multi-hop retrieval — and when it doesn't.
How AI Agents Navigate Knowledge Graphs
AI agent knowledge graph traversal depends on navigation policy, read-side tools, resolution, provenance, and stopping budget — not just graph size.
Hypergraph vs Hyperbolic Graph for AI Memory
Hypergraph vs hyperbolic graph for AI memory: one grows the edge to many vertices (n-ary); the other curves the space for hierarchy. Where Mnemoverse bets.
Building Memory That Scales
Building memory that scales: a memory engine from 0.116 to 0.862 on LoCoMo over seven versions, quality held at 14x growth, with a 3D graph to watch it grow.