| title: "Flood-Filling Agent Mesh (FFAM)" | |
| subtitle: "Applying Brain Connectomics to Multi-Agent AI Topology" | |
| authors: | |
| - name: "Yahya Saqban" | |
| affiliation: "HayulaLab" | |
| date: "July 2026" | |
| tags: | |
| - connectomics | |
| - multi-agent-systems | |
| - graph-theory | |
| - flood-filling-networks | |
| - agent-mesh | |
| - synthetic-graphs | |
| license: apache-2.0 | |
| # Flood-Filling Agent Mesh (FFAM) | |
| **Applying Brain Connectomics to Multi-Agent AI Topology** | |
| Inspired by Google Research's Neural Mapping project (Flood-Filling Networks, SegCLR, MoGen), FFAM maps multi-agent communication networks the same way neuroscientists map neural circuits. | |
| ## Features | |
| - 🧠 Agent Connectome Builder — Real-time graph of all agent communications | |
| - 🔍 Hub Detection — Find the most connected agents | |
| - ⚠️ Bottleneck Analysis — Identify single points of failure | |
| - 🛤️ Critical Path Tracing — Most common agent chains | |
| - 🧬 Synthetic Graph Generation — MoGen-inspired training data | |
| ## Quick Start | |
| ```bash | |
| python3 connectome.py demo | |
| ``` | |
| ## Paper | |
| 📄 [paper.md](./paper.md) — Full research paper | |
| ## Links | |
| - 📦 Gitea: https://git.hayula.xyz/y7/agent-connectome | |
| - 🌐 Website: https://hayula.xyz | |