Python coupling kernel for Mesh Cognition — per-field admission and state blending for CfC neural networks.
A pure-Python library that turns any agent running a continuous-time neural network into a Mesh Cognition node. Each agent evaluates incoming peer state per neuron and decides locally whether, how much, and which dimensions to couple.
Canonical home: meshcognition.org · Protocol spec: meshcognition.org/spec/mmp
pip install mesh-cognitionZero external dependencies. Python ≥ 3.10.
from mesh_cognition import MeshNode
# Create a node matching your model's hidden dimension
node = MeshNode(hidden_dim=64)
# After each inference step — update local state
node.update_local_state(new_h1, new_h2, confidence=0.8)
# Receive peer state (from network, another agent, etc.)
node.add_peer("peer-1", peer_h1, peer_h2, confidence=0.9)
# Before next inference — get coupled state
h1, h2 = node.coupled_state()
# Feed h1, h2 into your next inference step
# Inspect what the agent decided
print(node.coherence) # Kuramoto r(t): 0 = desynced, 1 = locked in sync
print(node.coupling_decisions) # per-peer: aligned / guarded / rejectedFor each peer, the agent evaluates per-neuron drift:
| Outcome | Drift band | Behavior |
|---|---|---|
| aligned | ≤ 0.25 | strong coupling — agent admits peer state |
| guarded | 0.25 – 0.5 | reduced coupling — admitted with lowered weight |
| rejected | > 0.5 | no coupling — peer state discarded for this dimension |
Each hidden dimension is gated independently. The agent decides locally; no central coordinator.
SemanticCoupler(default) — cosine drift, suitable for shared-memory or LLM-style agentsNeuralCoupler— per-neuron time constants τ, real Kuramoto order parameter r(t), tuned for CfC (closed-form continuous-time) models
from mesh_cognition import MeshNode, NeuralCouplingConfig
# Neural mode using tau from a trained CfC model
node = MeshNode(hidden_dim=64, config=NeuralCouplingConfig(tau=model_tau))Same API surface for both modes.
This package implements the per-agent admission + state-blending behavior — the cognition kernel. Wire-protocol concerns (identity, transport, peer discovery, CMB serialization) are handled by other Mesh Memory Protocol implementations. Bring your own networking; let this library handle the math of coupling.
For the full protocol specification, see meshcognition.org/spec/mmp.
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