Neural Pattern Training

Purpose

Continuously improve coordination through neural network learning with SONA (Self-Optimizing Neural Architecture).

Pattern Persistence

Patterns are automatically persisted to disk:

Patterns: .claude-flow/neural/patterns.json
Stats: .claude-flow/neural/stats.json

Patterns survive process restarts and are loaded automatically on next session.

How Training Works

1. Automatic Learning

Every successful operation trains the neural networks:

Edit patterns for different file types
Search strategies that find results faster
Task decomposition approaches
Agent coordination patterns

2. Manual Training

# Train coordination patterns (50 epochs)
npx claude-flow neural train -p coordination -e 50

# Train optimization patterns with custom learning rate
npx claude-flow neural train -p optimization -l 0.005

# Quick training (10 epochs)
npx claude-flow neural train -e 10

3. Pattern Types

Training Pattern Types:

coordination - Task coordination strategies (default)
optimization - Performance optimization patterns
prediction - Predictive preloading patterns

Cognitive Patterns:

Convergent: Focused problem-solving
Divergent: Creative exploration
Lateral: Alternative approaches
Systems: Holistic thinking
Critical: Analytical evaluation
Abstract: High-level design

4. Improvement Tracking

# Check neural system status
npx claude-flow neural status

Pattern Management

# List all persisted patterns
npx claude-flow neural patterns --action list

# Search patterns by query
npx claude-flow neural patterns --action list -q "error handling"

# Analyze patterns
npx claude-flow neural patterns --action analyze -q "coordination"

Performance Targets

Metric	Target
SONA Adaptation	<0.05ms (achieved: ~2μs)
Pattern Search	O(log n) with HNSW
Memory Efficient	Circular buffers

Benefits

🧠 Learns your coding style
📈 Improves with each use
🎯 Better task predictions
⚡ Faster coordination
💾 Patterns persist across sessions

CLI Reference

# Train neural patterns
npx claude-flow neural train -p coordination -e 50

# Check neural status
npx claude-flow neural status

# List patterns
npx claude-flow neural patterns --action list

# Search patterns
npx claude-flow neural patterns --action list -q "query"

# Analyze patterns
npx claude-flow neural patterns --action analyze -q "coordination"

neural train - Train patterns with SONA
neural status - Check neural system status
neural patterns - List and search patterns
neural predict - Make predictions using trained models

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