unwiring-arena
Play/Coplay arena theory for autopoietic closure with GF(3) conservation
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Install command
npx @skill-hub/cli install plurigrid-asi-unwiring-arena
Repository
Skill path: skills/unwiring-arena
Play/Coplay arena theory for autopoietic closure with GF(3) conservation
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Catalog source: SkillHub Club.
Repository owner: plurigrid.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
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- Install unwiring-arena into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/plurigrid/asi before adding unwiring-arena to shared team environments
- Use unwiring-arena for development workflows
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Original source / Raw SKILL.md
---
name: unwiring-arena
description: Play/Coplay arena theory for autopoietic closure with GF(3) conservation
version: 1.0.0
---
# Unwiring Arena Skill
**Status**: ✅ Production Ready
**Trit**: 0 (ERGODIC - balanced flow)
**Principle**: Play/Coplay autopoietic closure with GF(3) conservation
**Source**: plurigrid/UnwiringDiagrams.jl#1 + Capucci et al. Arena Theory
---
## Overview
**Unwiring Arena** unifies three categorical patterns:
1. **Wiring Diagrams** (AlgebraicJulia/Catlab) - Compositional system construction
2. **Unwiring Rules** (GayUncommonsSimulator) - Learning through constraint release
3. **Arena Protocol** (Plurigrid Amelia v0.4) - Play/Coplay bidirectional channels
```
┌─ Play Channel (Outbound) ─────────────────┐
│ Local arena mutations → NATS broadcast │
│ Strategy profiles → Action selection │
└────────────────────────────────────────────┘
↕ (Autopoietic closure)
┌─ Coplay Channel (Inbound) ───────────────┐
│ Peer arena submissions → Reconciliation │
│ Rewards/feedback → Identity update │
└────────────────────────────────────────────┘
```
## Mathematical Foundation
### Arenas as Parametrised Lenses
From Capucci, Ghani, Ledent, Forsberg:
```
Arena A_G : Lens_{(Ω,℧)}(X,S)(Y,R)
where:
Ω = Π_{p∈P} Ωₚ (strategy profiles)
℧ = Π_{p∈P} ℧ₚ (reward vectors)
X, Y = states
S, R = costates (feedback)
```
**Play**: `play_A : Ω × X → Y` (forward pass)
**Coplay**: `coplay_A : Ω × X × R → ℧ × S` (backward pass with feedback)
### Unwiring = Learning Through Constraint Release
```julia
struct UnwiringRule
source_gf3::Int # Source polarity {-1, 0, +1}
target_gf3::Int # Target polarity
learning_rate::Float64 # How fast to unwire
threshold::Float64 # Discrepancy threshold to trigger
end
# Unwiring shifts internal toward external (learning)
function apply_unwiring(rule, internal, external)
α = rule.learning_rate
return (1-α) * internal + α * external
end
```
### GF(3) Tripartite Channels
```
MINUS (-1) : Constraint verification (coplay focus)
ERGODIC (0) : Balance/coordination (arena equilibrium)
PLUS (+1) : Generative exploration (play focus)
Conservation: sum(trits) ≡ 0 (mod 3) per triplet
```
## Arena Protocol v0.4 (Amelia)
### Schema (JSONSchema v7)
```json
{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"arena_id": { "type": "string", "format": "uuid" },
"seed": { "type": "integer", "description": "SplitMix64 seed" },
"players": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": { "type": "string" },
"strategy_space": { "type": "array" },
"gf3_polarity": { "enum": [-1, 0, 1] }
}
}
},
"play_channel": {
"type": "object",
"properties": {
"topic": { "type": "string", "pattern": "^plurigrid\\.arena\\.play\\." },
"mutations": { "type": "array" }
}
},
"coplay_channel": {
"type": "object",
"properties": {
"topic": { "type": "string", "pattern": "^plurigrid\\.arena\\.coplay\\." },
"reconciliations": { "type": "array" }
}
}
}
}
```
### NATS Topics
```
plurigrid.arena.play.{agent}.{focus} # Outbound mutations
plurigrid.arena.coplay.{agent}.{focus} # Inbound feedback
plurigrid.arena.peers.> # Peer discovery
plurigrid.arena.reconcile # Conflict resolution
```
## Julia Implementation
### Core Types
```julia
using Catlab.WiringDiagrams
using Catlab.Programs
# Arena as parametrised lens
struct Arena{Ω, U, X, S, Y, R}
play::Function # Ω × X → Y
coplay::Function # Ω × X × R → U × S
strategies::Ω
rewards::U
end
# Unwiring rule for learning
struct UnwiringRule
source_gf3::Int
target_gf3::Int
learning_rate::Float64
threshold::Float64
end
# Agent with reafferent identity
mutable struct ArenaAgent
id::UInt64
internal_state::Vector{Float64}
external_observation::Vector{Float64}
discrepancy::Float64
gf3::Int
unwiring_count::Int
current_rule::Int
end
```
### Compositional Arena Construction
```julia
using Catlab.WiringDiagrams: WiringDiagram, add_box!, add_wire!
"""
Build arena wiring diagram from player specifications.
"""
function build_arena_diagram(players::Vector{Tuple{Symbol, Int}})
d = WiringDiagram([:X], [:Y])
for (name, arity) in players
box = add_box!(d, Box(name, fill(:strategy, arity), [:action]))
end
# Wire sequentially (can be customized)
for i in 1:(length(players)-1)
add_wire!(d, (i, 1) => (i+1, 1))
end
return d
end
"""
Unwire a connection (remove constraint, enable learning).
"""
function unwire!(d::WiringDiagram, wire_id::Int)
# Remove wire - allows independent evolution
delete_wire!(d, wire_id)
end
"""
Apply unwiring rule based on discrepancy.
"""
function apply_unwiring!(agent::ArenaAgent, rules::Vector{UnwiringRule})
rule = rules[agent.current_rule]
if agent.discrepancy > rule.threshold && agent.gf3 == rule.source_gf3
α = rule.learning_rate
agent.internal_state = (1-α) .* agent.internal_state .+
α .* agent.external_observation
agent.unwiring_count += 1
agent.current_rule = mod1(agent.current_rule + 1, length(rules))
end
update_identity!(agent)
end
```
### Play/Coplay Implementation
```julia
"""
Play: Forward pass through arena.
"""
function arena_play(arena::Arena, strategy::Ω, state::X) where {Ω, X}
arena.play(strategy, state)
end
"""
Coplay: Backward pass with reward feedback.
"""
function arena_coplay(arena::Arena, strategy::Ω, state::X, reward::R) where {Ω, X, R}
arena.coplay(strategy, state, reward)
end
"""
Autopoietic closure: play ∘ coplay cycle.
"""
function arena_cycle!(agent::ArenaAgent, arena::Arena, external_reward)
# Play: agent acts
action = arena_play(arena, agent.internal_state, agent.external_observation)
# Coplay: receive feedback, update internal state
utility, new_costate = arena_coplay(arena, agent.internal_state,
agent.external_observation, external_reward)
# Update discrepancy (reafference)
agent.external_observation = new_costate
agent.discrepancy = norm(agent.internal_state - agent.external_observation)
agent.gf3 = Int(hash(agent.internal_state) % 3) - 1
return action, utility
end
```
## Python Implementation
```python
"""
unwiring_arena.py - Arena Protocol with Unwiring Rules
"""
from dataclasses import dataclass, field
from typing import List, Callable, Tuple, Dict, Any
import numpy as np
# SplitMix64 constants
GOLDEN = 0x9E3779B97F4A7C15
MASK64 = (1 << 64) - 1
@dataclass
class UnwiringRule:
"""How identity transforms through learning."""
source_gf3: int # {-1, 0, +1}
target_gf3: int
learning_rate: float
threshold: float
UNWIRING_RULES = [
UnwiringRule(0, 1, 0.1, 0.2), # Fresh→Aging: slow learning
UnwiringRule(1, -1, 0.3, 0.4), # Aging→Stale: medium learning
UnwiringRule(-1, 0, 0.5, 0.6), # Stale→Fresh: fast learning (reset)
UnwiringRule(0, -1, 0.05, 0.8), # Fresh→Stale: rare leap
]
@dataclass
class ArenaAgent:
"""Agent with reafferent identity."""
id: int
internal_state: np.ndarray
external_observation: np.ndarray
discrepancy: float = 0.0
gf3: int = 0
unwiring_count: int = 0
current_rule: int = 0
def update_identity(self):
"""Recompute identity from internal/external discrepancy."""
self.discrepancy = np.linalg.norm(
self.internal_state - self.external_observation
)
h = hash(self.internal_state.tobytes())
self.gf3 = (h % 3) - 1
@dataclass
class Arena:
"""Parametrised lens for game-theoretic interaction."""
play: Callable # (strategy, state) -> action
coplay: Callable # (strategy, state, reward) -> (utility, costate)
def cycle(self, agent: ArenaAgent, external_reward: float) -> Tuple[Any, float]:
"""Execute play/coplay autopoietic cycle."""
# Play: forward pass
action = self.play(agent.internal_state, agent.external_observation)
# Coplay: backward pass with feedback
utility, new_costate = self.coplay(
agent.internal_state,
agent.external_observation,
external_reward
)
# Update agent's external observation
agent.external_observation = new_costate
agent.update_identity()
return action, utility
def apply_unwiring(agent: ArenaAgent, rules: List[UnwiringRule] = UNWIRING_RULES):
"""Apply unwiring rule to shift internal toward external."""
rule = rules[agent.current_rule]
if agent.discrepancy > rule.threshold and agent.gf3 == rule.source_gf3:
α = rule.learning_rate
agent.internal_state = (
(1 - α) * agent.internal_state +
α * agent.external_observation
)
agent.unwiring_count += 1
agent.current_rule = (agent.current_rule + 1) % len(rules)
agent.update_identity()
```
## NATS Integration
```python
import nats
import json
NATS_SERVER = "nats://nonlocal.info:4222"
async def publish_arena_play(nc, agent_id: str, focus: str, mutation: dict):
"""Publish play channel mutation."""
topic = f"plurigrid.arena.play.{agent_id}.{focus}"
await nc.publish(topic, json.dumps(mutation).encode())
async def subscribe_arena_coplay(nc, agent_id: str, handler):
"""Subscribe to coplay channel feedback."""
topic = f"plurigrid.arena.coplay.{agent_id}.>"
await nc.subscribe(topic, cb=handler)
async def broadcast_reconciliation(nc, arena_state: dict):
"""Broadcast arena state for reconciliation."""
await nc.publish("plurigrid.arena.reconcile", json.dumps(arena_state).encode())
```
## Integration with GayUncommonsSimulator
```julia
# From GayUncommonsSimulator.jl - the key insight
# Wiring = constraint (commons pooling)
# Unwiring = freedom (uncommons differentiation)
const UNWIRING_RULES = [
UnwiringRule(0, 1, 0.1, 0.2), # Fresh→Aging
UnwiringRule(1, 2, 0.3, 0.4), # Aging→Stale
UnwiringRule(2, 0, 0.5, 0.6), # Stale→Fresh (reset cycle)
]
# Identity IS discrepancy
struct ReafferentID
internal::RGB
external::RGB
discrepancy::Float64
hash::UInt64
gf3::Int
end
# ID = hash(internal ⊻ external)
function ReafferentID(internal::RGB, external::RGB)
disc = abs(spectrum_t(internal) - spectrum_t(external))
id_hash = mix(to_hash(internal) ⊻ to_hash(external))
gf3 = Int(id_hash % 3)
ReafferentID(internal, external, disc, id_hash, gf3)
end
```
## Chronoscope Video Integration
The Arena Protocol includes video orchestration for 69 demonstrations:
```julia
# 7 categories × ~10 videos each
CHRONOSCOPE_CATEGORIES = [
:categorical_ops, # Operad operations
:quantum, # ZX calculus
:hypergraph, # Hypergraph rewriting
:ducklake, # Time-travel queries
:embodied_gradualism, # Learning dynamics
:ontology, # Schema evolution
:arena_protocol, # This very protocol
]
# Deterministic scheduling with seed 1069
schedule_videos(seed=1069, categories=CHRONOSCOPE_CATEGORIES)
```
## Commands
```bash
# Julia - run arena simulation
julia -e "include(\"GayUncommonsSimulator.jl\"); simulate_wev(n_steps=100)"
# Python - NATS arena client
uv run --with nats-py arena_client.py
# Catlab wiring diagram
julia -e "using Catlab.WiringDiagrams; d = WiringDiagram([:X], [:Y])"
```
## Key Patterns
| Pattern | Wiring | Unwiring |
|---------|--------|----------|
| **Semantics** | Constraint | Freedom |
| **Direction** | Composition | Decomposition |
| **Learning** | Fixed relationship | Adaptive relationship |
| **GF3 Flow** | -1 (MINUS) | +1 (PLUS) |
## See Also
- [GayUncommonsSimulator.jl](file:///Users/bob/ies/GayUncommonsSimulator.jl) - Full implementation
- [plurigrid/UnwiringDiagrams.jl#1](https://github.com/plurigrid/UnwiringDiagrams.jl/pull/1) - Arena Protocol PR
- [Capucci et al.](file:///Users/bob/ies/paper_extracts/mathpix_snips/obsidian/math/M.%20Capucci,%20N.%20Ghani,%20J.%20Ledent,%20F.%20Nordvall%20Forsberg.md) - Arenas with players
- [gay-mcp](file:///Users/bob/.claude/skills/gay-mcp/SKILL.md) - Deterministic colors
- [triad-interleave](file:///Users/bob/.claude/skills/triad-interleave/SKILL.md) - GF(3) scheduling
## Thread History (Extracted Patterns)
### Core Arena/Games Threads
| Thread | Messages | Key Pattern |
|--------|----------|-------------|
| [GayUncommonsSimulator with reafference](https://ampcode.com/threads/T-019b22bf-11fd-73ad-a61a-e7c40373fd49) | 61 | ID = hash(internal ⊻ external), WEV extraction |
| [GAY protocol stack + open games](https://ampcode.com/threads/T-019b22cd-ef86-77eb-a285-8dbe2312558f) | 39 | 3-coloring guarantees, Hedges open games |
| [DiscoHy operadic framework](https://ampcode.com/threads/T-019b44e5-39bb-7251-a8fa-5d1efaa5dafa) | 55 | ParaLens, Hedges equilibria, operads |
| [Random walk spectral gap](https://ampcode.com/threads/T-019b43de-907c-7008-a545-57e8ff698498) | 104 | Open-games + active-inference GF(3) balance |
### Wiring/Category Threads
| Thread | Messages | Key Pattern |
|--------|----------|-------------|
| [Load acset skill](https://ampcode.com/threads/T-019b43a6-11f7-77a8-a9cd-ea618e457b70) | 88 | C-set as functor, DPO rewriting |
| [Formalize skills with interaction entropy](https://ampcode.com/threads/T-019b44d2-05db-72e2-9a4a-23b7e1085b25) | 61 | DisCoPy boxes, ACSet integration |
| [Install plurigrid ASI skills](https://ampcode.com/threads/T-019b44c6-bfa3-7371-b238-023eb308d12b) | 124 | SchOperadNetwork, morphism traversal |
| [P2P file exchange + skills](https://ampcode.com/threads/T-019b4464-a75b-714e-9f73-e4e1dfd82ab7) | 162 | DiscoPy operads, 1069 subscales |
### WEV/Value Extraction Threads
| Thread | Messages | Key Pattern |
|--------|----------|-------------|
| [Comprehensive GAY protocol](https://ampcode.com/threads/T-019b22d0-c29f-72e7-a229-57a99774d3fa) | 160 | 3-match guarantee, pigeonhole bound |
| [Find recent fork threads](https://ampcode.com/threads/T-019b22aa-e7ef-779c-9246-9977c1c6a9ae) | 150 | WEV formula, colored operad schema |
| [Self-reflexive triadic subagent](https://ampcode.com/threads/T-019b233a-7ddf-734c-b117-2dd65ae97a80) | 141 | Tripartite network, GF(3) conservation |
### Key Extracted Formulas
```julia
# WEV (World Extractable Value)
WEV(agent, world) = base_value × staleness_mult × scarcity_mult
where:
base_value = agent.discrepancy × 10.0
staleness_mult = 1.0 + Σ(days_since_asked) × 0.1
scarcity_mult = 1.0 + (1.0 - occupancy[color] / total)
# 3-Coloring Guarantees
∀ i: color[i] ≠ color[i+1] # Adjacent Distinct
∀ window of 3: {R, Y, B} all present # 3-Match Property
# Reafferent Identity
ID = hash(internal_color ⊻ external_color)
discrepancy = |spectrum_t(internal) - spectrum_t(external)|
```
### ACSet Schema for Arena Protocol
```julia
@present SchArenaProtocol(FreeSchema) begin
Agent::Ob
Arena::Ob
Channel::Ob
Message::Ob
agent_arena::Hom(Agent, Arena)
msg_channel::Hom(Message, Channel)
channel_arena::Hom(Channel, Arena)
# Attributes
Name::AttrType
Trit::AttrType
Seed::AttrType
agent_name::Attr(Agent, Name)
agent_trit::Attr(Agent, Trit)
arena_seed::Attr(Arena, Seed)
channel_type::Attr(Channel, Name) # "play" or "coplay"
end
```
---
**Skill Name**: unwiring-arena
**Type**: Compositional Game Theory / Learning
**Trit**: 0 (ERGODIC)
**GF(3)**: Play/Coplay closure maintains conservation
**SPI**: Deterministic arena fingerprints via seed chain
**Threads**: 15+ related threads with 1400+ combined messages
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Graph Theory
- **networkx** [○] via bicomodule
- Universal graph hub
### Bibliography References
- `general`: 734 citations in bib.duckdb
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
This ensures compositional coherence in the Cat# equipment structure.