wev-verification
1
总安装量
1
周安装量
#47448
全站排名
安装命令
npx skills add https://github.com/plurigrid/asi --skill wev-verification
Agent 安装分布
codex
1
claude-code
1
Skill 文档
WEV Verification Skill
Trit: -1 (MINUS – Validator)
GF(3) Triad: wev-verification (-1) â world-hopping (0) â alife (+1) = 0
Overview
World Extractable Value (WEV) verification connecting:
- Quadrant Chart (Colorable à Derangeable)
- Proof-of-Frog consensus
- Learning Agent reafference loops
- GF(3) conservation
WEV Formula
WEV = Σ(coordinated outcomes) - Σ(coordination costs)
Legacy: WEV = V - 0.5V - costs = 0.4V
GF(3): WEV = V + 0.1V - 0.01 = 1.09V
Advantage: 2.7x
Quadrant Classification
| Quadrant | Colorable | Derangeable | Examples |
|---|---|---|---|
| Q1 (OPTIMAL) | â | â | PR#18, Knight Tour |
| Q2 | â | â | Identity morphisms |
| Q3 (WORST) | â | â | Deadlock states |
| Q4 | â | â | Phase transitions |
Learning Agent Architecture
âââââââââââââââââââââââââââââââââââââââââââ
â Reafference Loop â
âââââââââââââââââââââââââââââââââââââââââââ¤
â 1. Predict (Efference Copy) â
â 2. Execute (Action) â
â 3. Observe (Sensation) â
â 4. Match? (Validate) â
â 5. Update Model (Learn) â
âââââââââââââââââââââââââââââââââââââââââââ
Usage
using .WEVVerification
# Quadrant verification
items = [
("PR#18", 0.85, 0.90),
("Knight Tour", 0.75, 0.85),
("Deadlock", 0.15, 0.15),
]
verify_quadrant(items)
# WEV comparison
comparison = compare_wev_legacy_vs_gf3(100.0)
println("Advantage: ", comparison.advantage)
# Learning agents
alice = LearningAgent(:alice, Int8(-1))
arbiter = LearningAgent(:arbiter, Int8(0))
bob = LearningAgent(:bob, Int8(1))
# Reafference loop
reafference_loop!(alice, action, world_state)
# Frog status
frog_status([alice, arbiter, bob])
Neighbors
High Affinity
world-hopping(0): Cross-world navigationalife(+1): Emergent behaviorcybernetic-immune(-1): Self/Non-Self
Example Triad
skills: [wev-verification, world-hopping, alife]
sum: (-1) + (0) + (+1) = 0 â CONSERVED
References
- Block Science KOI
- von Holst (1950) – Reafference principle
- Powers (1973) – Perceptual Control Theory
Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
Graph Theory
- networkx [â] via bicomodule
- Universal graph hub
Bibliography References
category-theory: 139 citations in bib.duckdb
SDF Interleaving
This skill connects to Software Design for Flexibility (Hanson & Sussman, 2021):
Primary Chapter: 10. Adventure Game Example
Concepts: autonomous agent, game, synthesis
GF(3) Balanced Triad
wev-verification (â) + SDF.Ch10 (+) + [balancer] (â) = 0
Skill Trit: -1 (MINUS – verification)
Secondary Chapters
- Ch4: Pattern Matching
- Ch2: Domain-Specific Languages
Connection Pattern
Adventure games synthesize techniques. This skill integrates multiple patterns.
Cat# Integration
This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: â
Kan Role: Adj
Color: #26D826
GF(3) Naturality
The skill participates in triads satisfying:
(-1) + (0) + (+1) â¡ 0 (mod 3)
This ensures compositional coherence in the Cat# equipment structure.