Helix-Agent
I've been building a continuously-running cognitive agent called Helix-AGI and I'm just looking to get some additional people involved with testing and development.
The main thing: instead of cosine similarity for retrieval, I'm using a physics-based gravity equation derived from Verlinde's entropic gravity:
score = T × mass / d²
Where T is a Lorentzian temperature decay (recency), mass is structural — confidence × (1 + connections/mean_connections) — and d is Euclidean distance in an 8D manifold projected from 384D embeddings via Johnson-Lindenstrauss. The result is that retrieval naturally integrates recency, structural importance, and semantic proximity without tuning separate weights for each.
The attention center moves through that manifold each pulse under Euler-Lagrange dynamics — gravity from nearby beliefs, a stability force tethering it to the identity center, and a stimulus force from new input. There's a damping coefficient γ that builds attentional momentum during sustained focus and resets on topic shifts.
A few other things worth mentioning:
- Pulse loop runs at 30s (active), 15min (resting), dormant 1am-6am. Autonomous thought during resting pulses, nightly UMAP/HDBSCAN clustering that synthesizes compound beliefs from episodic memory.
- Stability Sentinel tracks H(q) and D_KL from an identity center in real time. These directly modulate LLM temperature and context window — high cognitive drift drops temperature to 0.1 and restricts context to 50%.
- The system prompt is compiled dynamically from whichever self_identity beliefs have the most mass. It changes slowly as beliefs accumulate and decay.
- Memories encode a somatic snapshot at formation. Recalling a memory formed under stress mildly reproduces that stress via omega nudge. State-dependent recall.
- Local Ollama (Granite) handles belief detection post-pulse so that classification runs free on every pulse without API cost.
Solo project, independent dev, still early. Looking for people who want to poke at the physics implementation or test edge cases in the retrieval system. Technical specifications are in the Documents folder in the GitHub Repo.