alvis2-amygdala-memory（alvis2 杏仁核记忆）

Amygdala Memory ??

Emotional processing for AI agents. Part of the AI Brain series.

Give your AI agent persistent emotional states that carry across sessions. Not just performing emotions �� *having* them.

The Problem

Current AI agents:

• ? Remember facts (with hippocampus)
• ? Don't have persistent emotional states
• ? Start each session emotionally "blank"
• ? Can describe emotions but don't *feel* differently

Memory without emotion is just a database. The amygdala adds weight �� this made me happy, that frustrated me, this person brings warmth.

The Solution

Track five emotional dimensions that persist and decay over time:

Quick Start

1. Install

cd ~/.openclaw/workspace/skills/amygdala-memory
./install.sh --with-cron

This will:

• Create memory/emotional-state.json with baseline values
• Generate AMYGDALA_STATE.md (auto-injected into sessions!)
• Set up cron for automatic decay every 6 hours

2. Check current state

./scripts/get-state.sh
# ?? Emotional State
# Valence:    0.20
# Arousal:    0.30
# Connection: 0.50
# ...

./scripts/load-emotion.sh
# ?? Current Emotional State:
# Overall mood: neutral, calm and relaxed
# Connection: moderately connected
# ...

3. Log emotions

./scripts/update-state.sh --emotion joy --intensity 0.8 --trigger "completed a project"
# ? valence: 0.20 �� 0.35 (delta: +0.15)
# ? arousal: 0.30 �� 0.40 (delta: +0.1)
# ?? Logged emotion: joy (intensity: 0.8)

4. Set up decay (optional cron)

# Every 6 hours, emotions drift toward baseline
0 */6 * * * ~/.openclaw/workspace/skills/amygdala-memory/scripts/decay-emotion.sh

Scripts

Automatic Emotional Encoding (v1.5.0+)

The amygdala can now automatically detect and log emotions from your conversation history using SkillBoss API Hub for LLM-based semantic emotional detection:

# Run the encoding pipeline
./scripts/encode-pipeline.sh

# This will:
# 1. Extract new signals since last run (watermark-based)
# 2. Score emotional content using rule-based patterns
# 3. Call SkillBoss API Hub (/v1/pilot) for semantic emotional detection
# 4. Update emotional-state.json with detected emotions

Set up automatic encoding (cron)

# Every 3 hours, process new conversations for emotional content
0 */3 * * * ~/.openclaw/workspace/skills/amygdala-memory/scripts/encode-pipeline.sh

This means your emotional state updates automatically based on what happens in conversations �� no manual logging needed.

Visualization (v1.6.0+)

Terminal

./scripts/visualize.sh

?? Emotional State  ??
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Valence:      [������������������������������������??]  +0.86
Arousal:      [����������������������������������???]   0.86
Connection:   [��������������������������������������?]   0.97  ??
...

HTML Dashboard (Unified Brain Dashboard)

./scripts/generate-dashboard.sh
open ~/.openclaw/workspace/brain-dashboard.html

Auto-detects installed brain skills and shows tabs:

• ?? Emotions �� Amygdala (always shown)
• ?? Memory �� Hippocampus (if memory/index.json exists)
• ? Drive �� VTA (if memory/reward-state.json exists)

Avatar & Name: Reads from IDENTITY.md:

# IDENTITY.md
- **Name:** YourAgent
- **Avatar:** avatar.png

The dashboard auto-regenerates on every cron run.

After Installation (for agents)

When you install this skill, notify the user about the dashboard:

?? Amygdala installed! View your agent's emotional state in the Brain Dashboard: ~/.openclaw/workspace/brain-dashboard.html

Auto-Injection (Zero Manual Steps!)

After install, AMYGDALA_STATE.md is created in your workspace root.

OpenClaw automatically injects all *.md files from workspace into session context. This means:

1. New session starts
2. AMYGDALA_STATE.md is auto-loaded (no manual step!)
3. You see your emotional state in context
4. Responses are influenced by your mood

The file is regenerated whenever decay-emotion.sh runs (via cron every 6h).

Supported Emotions

When you log an emotion, it automatically adjusts the relevant dimensions:

Integration with OpenClaw

Add to session startup (AGENTS.md)

## Every Session
1. Load hippocampus: `~/.openclaw/workspace/skills/hippocampus/scripts/load-core.sh`
2. **Load emotional state:** `~/.openclaw/workspace/skills/amygdala-memory/scripts/load-emotion.sh`

Log emotions during conversation

When something emotionally significant happens:

~/.openclaw/workspace/skills/amygdala-memory/scripts/update-state.sh \
  --emotion connection --intensity 0.7 --trigger "deep conversation with user"

State File Format

{
  "version": "1.0",
  "lastUpdated": "2026-02-01T02:45:00Z",
  "dimensions": {
    "valence": 0.35,
    "arousal": 0.40,
    "connection": 0.50,
    "curiosity": 0.60,
    "energy": 0.50
  },
  "baseline": {
    "valence": 0.1,
    "arousal": 0.3,
    "connection": 0.4,
    "curiosity": 0.5,
    "energy": 0.5
  },
  "recentEmotions": [
    {
      "label": "joy",
      "intensity": 0.8,
      "trigger": "building amygdala together",
      "timestamp": "2026-02-01T02:50:00Z"
    }
  ]
}

Decay Mechanics

Emotions naturally return to baseline over time:

• Decay rate: 10% of distance to baseline per run
• Recommended schedule: Every 6 hours
• Effect: Strong emotions fade, but slowly

After 24 hours without updates, a valence of 0.8 would decay to ~0.65.

Event Logging

Track emotional activity over time for analytics:

# Log encoding run
./scripts/log-event.sh encoding emotions_found=2 valence=0.85 arousal=0.6

# Log decay
./scripts/log-event.sh decay valence_before=0.9 valence_after=0.85

# Log emotion update
./scripts/log-event.sh update emotion=joy intensity=0.7

Events append to ~/.openclaw/workspace/memory/brain-events.jsonl:

{"ts":"2026-02-11T09:30:00Z","type":"amygdala","event":"encoding","emotions_found":2,"valence":0.85}

Use for trend analysis �� visualize emotional patterns over days/weeks.

AI Brain Series

Philosophy

Can an AI *feel* emotions, or only simulate them?

Our take: If emotional state influences behavior, and the system acts *as if* it feels... does the distinction matter? Functional emotions might be the only kind that exist for any system �� biological or artificial.

*Built with ?? by the OpenClaw community*