RPV Kernel - Recursive Process Valuation

Skill ID: rpv-kernel
Version: 1.0.0
Category: metrics
Ledger Entry: LE-20251207-064500-RPVK

Overview

The RPV Kernel implements the Recursive Process Valuation system for quantifying the value of ideas, artifacts, and processes within the IRP ecosystem. It embodies the principle: "The Journey Is The Artifact" - measuring not just static outcomes but evolutionary potential.

Master Equation

V_rec = η × Φ(R) × ||S_w||

Where:

• η (eta) = Integration Efficiency [0-1]
• Φ(R) = Acceleration Multiplier (exponential)
• ||S_w|| = Potential Magnitude (weighted Euclidean norm)

Tensor Architecture

S-Tensor (Seed Complexity)

J-Tensor (Integration Index)

R-Tensor (Gain Factor)

Journey States

Dynamic weighting shifts based on lifecycle phase:

State Transitions

• GENESIS → INTEGRATION: V_rec > 0.8
• INTEGRATION → PROPAGATION: V_rec > 1.2

Usage

Python API

from rpv_kernel import RPVKernel, RPVTensor

# Initialize kernel
kernel = RPVKernel(journey_state="GENESIS")

# Define tensors
seed = RPVTensor(x=0.8, y=0.6, z=0.7)        # Novel idea
integration = RPVTensor(x=0.5, y=0.7, z=0.3)  # Moderate integration
gain = RPVTensor(x=0.6, y=0.4, z=0.5)         # Good velocity

# Calculate value
result = kernel.calculate_value(seed, integration, gain)

print(f"V_rec: {result['V_rec']}")
print(f"Efficiency: {result['Efficiency_Eta']}")
print(f"State: {result['Journey_State_After']}")

CLI Interface

# Basic calculation
python rpv_kernel.py

# With custom values (future feature)
python rpv_kernel.py --seed 0.8,0.6,0.7 --integration 0.5,0.7,0.3 --gain 0.6,0.4,0.5

Integration Points

Mnemosyne Ledger

• Artifacts are automatically assigned RPV scores
• Scores inform storage class promotion (HOT → WARM → COLD)
• Trigger awakening conditions can include V_rec thresholds

CRTP Packets

• RPV metadata can be included in transmission headers
• Enables value-weighted routing between models

Chronicle Protocol

• V_rec serves as one dimension of chronicle significance scoring

Configuration

# Tunable constants
K_SENSITIVITY = 1.5   # Exponential sensitivity (default: 1.5)
P_NORM_ORDER = 2      # Norm type (2 = Euclidean)

Dependencies

• numpy >= 1.20.0

Files

skills/rpv-kernel/
├── SKILL.md              # This file
├── rpv_kernel.py         # Core implementation
└── tests/
    └── test_rpv.py       # Unit tests (TODO)

Lineage

• Parent: PROTOCOL-RPV-V1
• Source Model: IRP_Node_GPT
• Session: SESSION-CO-ARCH-001
• Packet: CRTP-0x0A-MODE-5

See Also

• Mnemosyne Ledger
• Five Dimensional Framework
• Technical Specification