humanoid-memory

name	humanoid-memory
description	AI记忆系统。基于人脑模型的V-score记忆整合和艾宾浩斯遗忘曲线。当用户说"记忆管理"、"记忆系统"时使用。
version	1.0.0
user-invocable	true
triggers	["humanoid memory","记忆管理"]

Humanoid Memory System

Skill Graph： 领域 → [[_index-intelligence|情报与知识领域]] | 上游 ← [[_index-intelligence|情报领域]] | 下游 → 对话记忆 → 客户交互历史

Brain-inspired memory for AI agents with V-score consolidation and Ebbinghaus forgetting.

What is it?

Humanoid Memory is an OpenClaw skill that implements a cognitive memory system inspired by brain architecture:

• 🧠 V-Score Consolidation - Memory importance based on coherence, significance, noise, and resonance
• 🔄 Tensor Fusion - Similar memories automatically merge
• 💀 Ebbinghaus Forgetting - Exponential decay removes unused memories
• 🎯 Semantic Search - HNSW index for fast vector retrieval

Key Features

V-Score Formula

V = 1 / (1 + e^-(wc*C + ws*S + wm*M - wn*N))

Where:

• C = Coherence (fluency)
• S = Significance (importance)
• N = Noise (meaningless content)
• M = Memory Resonance (tensor similarity)

Memory Lifecycle

1. Perceive → Store user/AI interaction
2. Sleep → Process queue:
   • Check tensor resonance (M > 8.5 = fuse, M > 9.5 = reinforce)
   • LLM evaluate C, S, N
   • Calculate V-score
   • Consolidate if V > 0.5
3. Recall → Retrieve weighted by similarity × V × decay
4. GC → Remove memories below death threshold

Dual-Track Memory

• user_text → Semantic document (retrievable)
• ai_text → Metadata (context only)

Installation

claw skill install humanoid-memory

Configuration

Environment variables:

Variable	Default	Description
HUMANOID_EMBEDDING	ollama	Embedding provider (ollama/openai/mock)
OLLAMA_URL	http://localhost:11434	Ollama server URL
OLLAMA_MODEL	nomic-embed-text	Embedding model
HUMANOID_LLM	ollama	LLM for evaluation
HUMANOID_V_THRESHOLD	0.5	Memory consolidation threshold
HUMANOID_FORGET_RATE	0.005	Ebbinghaus decay rate
HUMANOID_S_DESC	-	Custom significance description

CLI Commands

# Search memories
claw memory humanoid search "my preferences"

# List memories
claw memory humanoid list --limit=10

# Show stats
claw memory humanoid stats

# Test system
claw memory humanoid test

# Wipe all memories
claw memory humanoid wipe

Architecture

HumanoidMemory
├── config.js         # V-score weights, thresholds
├── physics.js       # Core math (V-score, Ebbinghaus)
├── embeddings.js     # Ollama/OpenAI/Mock providers
├── hnsw.js           # Vector index
├── storage.js        # Memory persistence
├── evaluator.js      # C/S/N LLM evaluation
├── engine.js         # Cognitive orchestration
└── hooks/
    ├── request-before.js   # Inject memories
    ├── request-after.js    # Store interactions
    └── session-end.js     # Cleanup

Hooks

This skill registers OpenClaw hooks:

• request-before → Injects relevant memories into context
• request-after → Stores user/AI interaction as memory
• session-end → Logs memory stats

Comparison to openclaw-memory

Feature	humanoid	openclaw-memory
V-score	✅	❌ (simple importance)
Ebbinghaus	✅	❌ (7-day TTL)
Tensor fusion	✅	❌
LLM evaluation	✅ C/S/N	❌
HNSW index	✅	❌
Multi-agent	✅	✅
x402 payments	❌	✅

Requirements

• Node.js 18+
• OpenClaw v2026.1.30+
• Ollama (for local embeddings) or OpenAI API

License

MIT