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genpark-personal-agent-neuroplasticity-synaptic-pruning-sleep-skill

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Guvenlik Denetimi
Uyari
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  • License — License: MIT
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SUMMARY

Models Tononi-Cirelli Synaptic Homeostasis (SHY), evaluates Slow-Wave Sleep delta down-scaling efficiency, and schedules Targeted Memory Reactivation (TMR).

README.md

Personal Agent Neuroplasticity Synaptic Pruning Sleep Skill

OpenClaw Ecosystem
Dual-Org Sync
Zero Dependencies
Model Context Protocol
Production Grade

Zero-dependency Tononi-Cirelli Synaptic Homeostasis Hypothesis (SHY) modeler, slow-wave sleep (SWS) down-selection renormalizer, and Targeted Memory Reactivation (TMR) scheduler.

Architecture

flowchart TD
    WakeEncoding[Wakeful Learning Hours & Novelty Intensity] --> PotentiationEngine[Synaptic Potentiation Load Engine]
    PotentiationEngine --> SaturationLevel[Synaptic Saturation Level %]
    SWSSleep[Slow-Wave Sleep Delta Duration Hours] --> SHYRenormalizer[SHY Down-Selection Renormalizer]
    SaturationLevel & SWSSleep --> RenormalizationEfficiency[Overnight Reset Efficiency & SNR Boost %]
    CoreLearning[Core Concepts to Retain] --> TMREngine[Targeted Memory Reactivation Scheduler]
    TMREngine --> PreSleepCues[25-Min Pre-Sleep Retrieval & Olfactory Anchor]

Quickstart

from client import PersonalAgentNeuroplasticitySynapticPruning

agent = PersonalAgentNeuroplasticitySynapticPruning()
res = agent.model_synaptic_homeostasis_scaling(waking_learning_hours=14.0, slow_wave_sleep_hours=1.8)
print(f"Renormalization: {res['overnight_synaptic_renormalization_efficiency']} | SNR Boost: {res['signal_to_noise_ratio_boost']}")

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