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Ontology Asi Interleave
DSecurity> Bridge connecting plurigrid/ontology to ASI skill graph. Wires autopoietic ergodicity, Open Games, Gromov-Wasserstein theory, Arena CRDT, Nexus Nodes, and transactive energy into decentralized energy coordination, digital twin multi-agent systems, and grid intelligence. Use when connecting ontology concepts to ASI skills, designing transactive energy markets, or bridging Arena CRDT to DuckDB. >>>>>>> origin/main
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[](https://www.skillsdirectory.com/skills/plurigrid-ontology-asi-interleave)---
name: ontology-asi-interleave <<<<<<< HEAD
description: '> Bridge connecting plurigrid/ontology to ASI skill graph. Wires autopoietic ergodicity, Open Games, Gromov-Wasserstein theory, Arena CRDT, Nexus Nodes, and transactive energy into decentralized energy coordination, digital twin multi-agent systems, and grid intelligence. Use when connecting ontology concepts to ASI skills, designing transactive energy markets, or bridging Arena CRDT to DuckDB. >>>>>>> origin/main'
deployed: 2026-02-19 =======
role: BRIDGE
tags: '[ontology, autopoiesis, ergodicity, open-games, gromov-wasserstein, crdt, arena, digital-twin, nexus-nodes, transactive-energy, gf3, interleave]'
trit: '0'
version: 1.0.0
---
# Ontology x ASI Interleave
Bridge connecting `plurigrid/ontology` (the Plurigrid protocol's mathematical and systems foundation) to the ASI skill graph.
## plurigrid/ontology -- 7 Core Concepts
```
<<<<<<< HEAD
plurigrid/ontology
1. Autopoietic Ergodicity -- self-org + time-avg = ensemble-avg convergence
2. Open Games Framework -- compositional game theory, Markov categories
3. Gromov-Wasserstein Theory -- metric measure space comparison, entropic reg.
4. Arena System -- local-first graph DB, Rust + Yrs CRDTs, DuckDB
5. Digital Twin Architecture -- multi-agent value elicitation, mutual recursion
6. Nexus Nodes -- 3-tier hardware: Apple Silicon / RPi4 / Pico W
7. Transactive Energy -- stigmergic markets, multi-agent RL + Open Games
```
## GF(3) Tripartite Tag
`arena-crdt(-1) * ontology-asi-interleave(0) * open-games(+1) = 0`
Infrastructure (-1) x Bridge (0) x Strategy (+1) = balanced energy coordination.
---
=======
1. Autopoietic Ergodicity -- self-org + time-avg = ensemble-avg convergence
2. Open Games Framework -- compositional game theory, Markov categories
3. Gromov-Wasserstein Theory -- metric measure space comparison, entropic reg.
4. Arena System -- local-first graph DB, Rust + Yrs CRDTs, DuckDB
5. Digital Twin Architecture -- multi-agent value elicitation, mutual recursion
6. Nexus Nodes -- 3-tier hardware: Apple Silicon / RPi4 / Pico W
7. Transactive Energy -- stigmergic markets, multi-agent RL + Open Games
```
>>>>>>> origin/main
## Integration Points
### 1. Autopoietic Ergodicity <-> autopoiesis, ergodicity, dynamic-sufficiency
<<<<<<< HEAD
Ontology defines autopoietic ergodicity as the convergence criterion: a system that self-organizes (autopoiesis) such that time averages equal ensemble averages (ergodicity), minimizing surprise through continuous learning (active inference).
```
ontology ASI skills
+-----------------------+ +-------------------------+
| autopoietic ergodicity|------->| autopoiesis |
| time-avg = ens-avg |------->| ergodicity |
| minimize surprise |------->| dynamic-sufficiency(145)|
| embodied gradualism | | active-inference |
+-----------------------+ +-------------------------+
```
`dynamic-sufficiency` (145 references, central hub) is the primary landing point: it already connects autopoiesis and ergodicity within ASI. Ontology's "embodied gradualism" maps to dynamic-sufficiency's gradual capability accumulation.
=======
A system that self-organizes (autopoiesis) such that time averages equal ensemble averages (ergodicity), minimizing surprise through continuous learning (active inference).
`dynamic-sufficiency` (145 references, central hub) is the primary landing point. Ontology's "embodied gradualism" maps to dynamic-sufficiency's gradual capability accumulation.
>>>>>>> origin/main
### 2. Open Games Framework <-> open-games, cybernetic-open-game
The Plurigrid protocol IS a compositional open game. Agents are morphisms in a Markov category with generative (play) and recognition (coplay) channels.
<<<<<<< HEAD
```
ontology ASI skills
+-----------------------+ +-------------------------+
| Open Games |------->| open-games |
| Markov categories |------->| cybernetic-open-game |
| correlated equilib. |------->| equilibrium |
| sense-making / AI |------->| nashator (9999) |
+-----------------------+ +-------------------------+
```
=======
>>>>>>> origin/main
Grid = composed game: `node_game @ transmission_game @ market_game`. The correlated equilibrium = autopoietically ergodic state = Nash equilibrium that is also thermodynamically stable.
### 3. Gromov-Wasserstein Theory <-> gflownet, duckdb-spatial
<<<<<<< HEAD
GW theory compares metric measure spaces and does graph matching across heterogeneous energy networks. Entropic regularization + Bregman projections for efficient optimization.
```
ontology ASI skills
+-----------------------+ +-------------------------+
| Gromov-Wasserstein |------->| gflownet (OT sampling) |
| entropic reg. |------->| duckdb-spatial (graphs) |
| Bregman projections |------->| geohash-coloring |
| graph matching |------->| map-projection |
+-----------------------+ +-------------------------+
```
GFlowNet samples from energy-proportional distributions over combinatorial structures -- the same optimal transport problem that GW solves for network matching. The entropic regularization in GW parallels the entropy bonus in GFlowNet training.
=======
GW theory compares metric measure spaces and does graph matching across heterogeneous energy networks. Entropic regularization + Bregman projections for efficient optimization. GFlowNet samples from energy-proportional distributions over combinatorial structures -- the same optimal transport problem that GW solves for network matching.
>>>>>>> origin/main
### 4. Arena CRDT System <-> crdt, time-travel-crdt, duckdb-ies
Arena is a local-first graph-based data store in Rust with DuckDB backend and Yrs CRDTs for real-time peer synchronization.
<<<<<<< HEAD
```
ontology ASI skills
+-----------------------+ +-------------------------+
| Arena System | | |
| Yrs (Y-CRDT) |------->| crdt |
| peer sync |------->| time-travel-crdt |
| DuckDB backend |------->| duckdb-ies |
| graph store |------->| duckdb-spatial |
| nodes/edges tables |------->| duckdb-quadruple-interl.|
+-----------------------+ +-------------------------+
```
Arena schema: `nodes(id, label, properties)` + `edges(id, src, dst, label, properties)` -- maps directly to DuckDB graph patterns in `duckdb-ies` and `duckdb-spatial`. The CRDT layer (Yrs) provides exactly the merge semantics that `time-travel-crdt` formalizes for ASI skill state.
### 5. Digital Twin Architecture <-> dynamic-sufficiency, agent-o-rama
Virtual representations of physical entities. Multi-agent loop in Chat Arena. Agent profiles with value systems and behavior models. Value elicitation via mutual recursion.
```
ontology ASI skills
+-----------------------+ +-------------------------+
| Digital Twin |------->| dynamic-sufficiency |
| agent profiles |------->| agent-o-rama (hub) |
| value elicitation |------->| cognitive-surrogate |
| active inference |------->| active-inference |
| mutual recursion |------->| skill-dispatch |
+-----------------------+ +-------------------------+
```
The digital twin's active inference loop (predict -> act -> observe -> update) is the same loop that `dynamic-sufficiency` implements for ASI skill selection. Each agent twin maintains a GF(3)-colored value system that evolves via CRDT merge with peer twins.
### 6. Nexus Nodes <-> hvm-runtime, world-runtime, iot-device-provisioning
3-tier hardware architecture, all targeting wasm32-unknown-unknown with WASI + capability plugins:
```
Tier Hardware Compute ASI Skill
+-----------+------------------+-------------+-------------------------+
| High Power| Apple Silicon | Full WASM | hvm-runtime |
| | (M-series Mac) | + TF ext. | world-runtime-capability|
+-----------+------------------+-------------+-------------------------+
| Low Power | Raspberry Pi 4 | WASI core | iot-device-provisioning |
| | (4GB ARM) | | |
+-----------+------------------+-------------+-------------------------+
| Embedded | RPi Pico W | Minimal WASI| iot-device-provisioning |
| | (264KB SRAM) | (sensor hub)| |
+-----------+------------------+-------------+-------------------------+
Runtime: WasmEdge for high-perf WASM with TensorFlow extensions
```
`hvm-runtime` handles the high-performance interaction net reduction on Apple Silicon. `world-runtime-capability` provides the capability-secure plugin system that maps to WASI capability plugins. `iot-device-provisioning` covers the provisioning and attestation workflow for the Low Power and Embedded tiers.
### 7. Transactive Energy <-> nashator, open-games, equilibrium
Market-based transactions between energy grids. Stigmergic feedback for energy availability, demand, and prices. Multi-agent RL + mutual information optimization + Open Games.
```
ontology ASI skills
+-----------------------+ +-------------------------+
| Transactive Energy |------->| nashator (market engine) |
| stigmergic feedback |------->| open-games (formalism) |
| market clearing |------->| equilibrium (solver) |
| multi-agent RL |------->| gym (RL environments) |
| mutual info opt. |------->| gflownet (sampling) |
+-----------------------+ +-------------------------+
```
Nashator at 127.0.0.1:9999 is the direct implementation target: each energy node submits bids as open game moves, the Nashator resolves to correlated equilibrium = market clearing price.
---
## Gap Registry
Capabilities in plurigrid/ontology not yet covered by ASI skills:
| Ontology Concept | Gap | Priority | Candidate Skill Name |
|-----------------|-----|----------|---------------------|
| Gromov-Wasserstein distance | No dedicated GW/OT skill; gflownet is tangential | HIGH | `gromov-wasserstein` |
| Arena graph store (Rust+Yrs) | No Rust CRDT skill; `crdt` is language-agnostic | MED | `arena-crdt` |
| Stigmergic feedback loops | No stigmergy skill; nashator handles markets only | MED | `stigmergy` |
| WasmEdge runtime | `hvm-runtime` covers HVM, not WasmEdge specifically | LOW | `wasmedge-runtime` |
| Value elicitation protocols | `dynamic-sufficiency` is close but not explicit | LOW | `value-elicitation` |
| Embodied gradualism | Philosophical concept; `autopoiesis` partially covers | LOW | (extend autopoiesis) |
| RPi Pico W sensor hub | `iot-device-provisioning` exists but no Pico W target | LOW | (extend iot-device) |
---
## Plurigrid Protocol Summary
The Plurigrid protocol = self-rebalancing, self-infrastructuring electricity grid:
=======
Arena schema: `nodes(id, label, properties)` + `edges(id, src, dst, label, properties)` -- maps directly to DuckDB graph patterns.
### 5. Digital Twin Architecture <-> dynamic-sufficiency, agent-o-rama
The digital twin's active inference loop (predict -> act -> observe -> update) is the same loop that `dynamic-sufficiency` implements for ASI skill selection.
### 6. Nexus Nodes <-> hvm-runtime, world-runtime, iot-device-provisioning
3-tier hardware architecture targeting wasm32-unknown-unknown with WASI + capability plugins:
| Tier | Hardware | Compute | ASI Skill |
|---|---|---|---|
| High Power | Apple Silicon (M-series) | Full WASM + TF ext. | hvm-runtime |
| Low Power | Raspberry Pi 4 (4GB ARM) | WASI core | iot-device-provisioning |
| Embedded | RPi Pico W (264KB SRAM) | Minimal WASI | iot-device-provisioning |
Runtime: WasmEdge for high-perf WASM with TensorFlow extensions.
### 7. Transactive Energy <-> nashator, open-games, equilibrium
Market-based transactions between energy grids. Stigmergic feedback for energy availability, demand, and prices.
Nashator at 127.0.0.1:9999 is the direct implementation target: each energy node submits bids as open game moves, the Nashator resolves to correlated equilibrium = market clearing price.
## Concrete Affordances
### Arena CRDT Schema in DuckDB
Create the Arena graph schema and insert sample energy-grid nodes:
```sql
-- File: /Users/alice/v/asi/skills/ontology-asi-interleave/arena_schema.sql
-- Run: duckdb /Users/alice/v/arena.duckdb < arena_schema.sql
CREATE TABLE IF NOT EXISTS arena_nodes (
id VARCHAR PRIMARY KEY,
label VARCHAR NOT NULL,
properties JSON,
created_at TIMESTAMP DEFAULT current_timestamp,
yrs_clock BIGINT DEFAULT 0 -- Yrs CRDT logical clock
);
CREATE TABLE IF NOT EXISTS arena_edges (
id VARCHAR PRIMARY KEY,
src VARCHAR NOT NULL REFERENCES arena_nodes(id),
dst VARCHAR NOT NULL REFERENCES arena_nodes(id),
label VARCHAR NOT NULL,
properties JSON,
weight DOUBLE DEFAULT 1.0
);
-- Sample: three Nexus Nodes forming a transactive energy triangle
INSERT OR IGNORE INTO arena_nodes VALUES
('nexus-m4', 'apple-silicon', '{"tier":"high","watt_capacity":150}', now(), 1),
('nexus-rpi', 'rpi4', '{"tier":"low","watt_capacity":15}', now(), 1),
('nexus-pico','pico-w', '{"tier":"embedded","watt_capacity":1}', now(), 1);
INSERT OR IGNORE INTO arena_edges VALUES
('e1', 'nexus-m4', 'nexus-rpi', 'energy-link', '{"latency_ms":2}', 1.0),
('e2', 'nexus-rpi', 'nexus-pico', 'energy-link', '{"latency_ms":50}', 0.5),
('e3', 'nexus-pico','nexus-m4', 'energy-link', '{"latency_ms":45}', 0.3);
-- Query: neighbor energy capacity
SELECT n.id, n.label, n.properties->>'watt_capacity' AS watts,
COUNT(e.id) AS degree
FROM arena_nodes n
LEFT JOIN arena_edges e ON n.id = e.src OR n.id = e.dst
GROUP BY n.id, n.label, watts;
```
### Nashator Transactive Energy API
Submit energy bids and query equilibrium via the Nashator service:
```bash
# Check Nashator is running
curl -s http://127.0.0.1:9999/health
# Submit an energy bid (open game move)
curl -X POST http://127.0.0.1:9999/api/v1/bid \
-H 'Content-Type: application/json' \
-d '{
"node_id": "nexus-m4",
"bid_type": "supply",
"quantity_kwh": 5.0,
"price_per_kwh": 0.12,
"timestamp": "'"$(date -u +%Y-%m-%dT%H:%M:%SZ)"'"
}'
# Query current correlated equilibrium (market clearing price)
curl -s http://127.0.0.1:9999/api/v1/equilibrium | python3 -m json.tool
```
### Open Games Grid Model (Julia)
Compose a transactive energy game using Open Games:
```julia
# Requires: using Pkg; Pkg.add(["OpenGames", "Catlab"])
using OpenGames, Catlab
# Each Nexus Node is a player choosing (quantity, price)
node_game = OpenGame(
name = :nexus_node,
strategies = [(0.0:0.5:10.0, 0.05:0.01:0.30)], # (kWh, $/kWh)
payoff = (s, ctx) -> s[2] * s[1] - generation_cost(s[1])
)
# Transmission: pairwise latency cost
transmission_game = OpenGame(
name = :transmission,
payoff = (s, ctx) -> -ctx[:latency_ms] * 0.001 * s[:quantity]
)
# Compose: node @ transmission @ market
grid_game = compose(node_game, transmission_game)
# Find Nash equilibrium via Lemke-Howson or support enumeration
eq = solve(grid_game, method=:support_enumeration)
println("Equilibrium price: ", eq.clearing_price, " \$/kWh")
```
### Gromov-Wasserstein Network Matching (Python)
Compare two energy network topologies using entropic GW distance:
```python
# pip install pot numpy
import numpy as np
import ot
# Adjacency / cost matrices for two energy networks
C1 = np.array([[0, 1, 0], [1, 0, 1], [0, 1, 0]], dtype=float) # linear
C2 = np.array([[0, 1, 1], [1, 0, 1], [1, 1, 0]], dtype=float) # triangle
p = ot.unif(C1.shape[0])
q = ot.unif(C2.shape[0])
# Entropic Gromov-Wasserstein distance
gw_dist, log = ot.gromov.entropic_gromov_wasserstein2(
C1, C2, p, q, loss_fun='square_loss', epsilon=0.1, log=True
)
print(f"Entropic GW distance: {gw_dist:.6f}")
print(f"Transport plan:\n{log['T']}")
```
## Gap Registry
| Ontology Concept | Gap | Priority | Candidate Skill |
|---|---|---|---|
| Gromov-Wasserstein distance | No dedicated GW/OT skill | HIGH | `gromov-wasserstein` |
| Arena graph store (Rust+Yrs) | No Rust CRDT skill | MED | `arena-crdt` |
| Stigmergic feedback loops | No stigmergy skill | MED | `stigmergy` |
| WasmEdge runtime | hvm-runtime covers HVM, not WasmEdge | LOW | `wasmedge-runtime` |
## Plurigrid Protocol Summary
>>>>>>> origin/main
- **Math core**: Open Games + Gromov-Wasserstein + Active Inference
- **Data layer**: Arena (local-first CRDT graph DB, Rust + Yrs + DuckDB)
- **Agent arch**: Digital twins with value elicitation + mutual recursion
- **Equilibrium**: Autopoietically ergodic state = Nash eq. that is thermodynamically stable
<<<<<<< HEAD
- **Energy market**: Stigmergic feedback -> decentralized price discovery -> transactive coordination
- **Hardware**: Nexus Nodes (Apple Silicon / RPi4 / Pico W) all running WASI
## Related Skills
- `autopoiesis` -- self-organization; the Plurigrid node model
- `ergodicity` -- time-average = ensemble-average convergence criterion
- `dynamic-sufficiency` -- 145-ref hub; autopoiesis + ergodicity nexus
- `open-games` -- compositional game theory; Plurigrid protocol formalization
- `cybernetic-open-game` -- cybernetic feedback in open game frameworks
- `crdt` / `time-travel-crdt` -- Arena CRDT patterns for distributed skill state
- `duckdb-ies` / `duckdb-spatial` -- Arena DuckDB backend patterns
- `gflownet` -- energy-proportional sampling; GW optimal transport analog
- `hvm-runtime` -- high-perf WASM on Apple Silicon Nexus tier
- `world-runtime-capability` -- WASI capability plugin system
- `iot-device-provisioning` -- Nexus Nodes Low Power + Embedded tiers
- `nashator` -- transactive energy market engine (127.0.0.1:9999)
- `agent-o-rama` -- universal hub; digital twin orchestration
- `equilibrium` -- Nash/correlated equilibria solver
- `ordered-locale` -- GF(3)->GF(9)->GF(27) tower; mathematical spine
- `catcolab-stock-flow` / `catcolab-causal-loop` -- energy system modeling
- `vertex-asi-interleave` / `bigquery-asi-interleave` -- sibling GCP bridges
=======
- **Energy market**: Stigmergic feedback -> decentralized price discovery
- **Hardware**: Nexus Nodes (Apple Silicon / RPi4 / Pico W) all running WASI
>>>>>>> origin/main
Files in this skill
- CONCOMITANT_SKILLS.md
- SKILL.md
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