| name | stigmergic-diffusion-medium |
| version | 0.1.0 |
| description | A graph-based shared blackboard where agents coordinate indirectly by depositing typed pheromone traces (PHEROMONE, BELIEF, PREFERENCE, ANTIBODY, RESOLUTION) onto graph nodes, then sensing and following concentration gradients. Traces spread via Euler-stable Laplacian diffusion and decay exponentially, creating a self-organizing signal field that replaces message buses, central planners, and explicit agent-to-agent communication. The coordination substrate for the SOMA multi-agent architecture (Week 1 kernel, extended by Active Inference agents in Week 2+).
|
| author | soma-windags-graft |
| tags | ["stigmergy","multi-agent","coordination","diffusion","graph","blackboard","active-inference","pheromone"] |
| pairs-with | ["active-inference-agent","belief-market-tateonnement","immune-selection-pressure"] |
| license | Apache-2.0 |
| allowed-tools | Read,Write,Edit,Glob,Grep |
| metadata | {"provenance":{"kind":"imported","source":"workgroup-ai / windags skill library (rehomed 2026-07-04)"}} |
Stigmergic Diffusion Medium
When to Use
- You need agents to coordinate without direct messaging: no queues, no RPC, no shared
mutable state beyond the medium itself. Agents write traces; other agents sense them.
- Your problem maps naturally onto a graph (import dependency graph, task DAG, knowledge
graph, file system, network topology) and agents need to discover high-value nodes by
following concentration signals rather than being assigned work.
- You want emergent load balancing and exploration: resolution traces dampen overcrowded
nodes; urgency amplification surfaces deadline pressure; antibody traces suppress
already-solved sub-problems — all without a scheduler.
NOT for:
- Hard real-time coordination where sub-millisecond synchronization is required (diffusion
physics introduce lag proportional to graph diameter).
- Problems where agents must exchange structured messages with guaranteed delivery — the
medium is a lossy signal field, not a reliable message bus.
- Flat, unstructured data with no natural graph topology; forcing one creates spurious
gradient artifacts.
Core Concepts
Trace (Trace dataclass): A single stigmergic deposit with fields trace_type,
intensity, depositor, created_at, optional deadline/urgency_alpha/urgency_beta
for temporal pressure, and optional confidence_stake/proposition for belief-market
extension. The fundamental write unit.
TraceType (enum): Five distinct "goods" in the wide-market framework —
PHEROMONE (work-in-progress / distress), BELIEF (probabilistic claims),
PREFERENCE (Active Inference priors, desired future states), ANTIBODY
(known-bad / already-solved patterns, triggers negative selection), RESOLUTION
(anti-inflammatory: suppresses agent activity at a node after a problem is closed).
Euler-stable Laplacian diffusion: At each tick, pheromone spreads along edges
via the discrete graph Laplacian Δp_v = Σ_{u~v}(p_u - p_v). To guarantee stability
under explicit Euler integration the effective step size is clamped:
dt_eff = min(dt, 0.9 / (diffusion_rate * max_degree)). Without this clamp,
high-degree hubs cause numerical blowup.
Pheromone gradient (gradient(node_id)): The discrete exterior derivative of the
pheromone 0-cochain restricted to the star of a vertex:
. Positive values attract; agents climb the gradient
toward higher concentrations. This is the only mechanism agents need to follow crowd
wisdom without knowing who deposited what.
