Cognitive Processes Research
Last Updated: 2026-02-06
Content-Type: Explanation
Audience: All
Primary Source: Research on human cognitive processes
Related System: Prompt System
Overview
This research explores how the human brain processes information from receiving input (what another person says/does) to generating a response. Understanding these processes helps design more aware, human-like AI systems through better prompt engineering.
The goal is to model cognitive processes in AI systems to create responses that are more natural, contextually appropriate, and emotionally aware.
Key Features
- 12 Cognitive Stages - Complete breakdown from sensory reception to feedback & learning
- Dual Process Theory - Fast (System 1) vs. Deliberate (System 2) processing pathways
- Visual Diagrams - Mermaid diagrams showing process flows and system architecture
- Implementation Guide - Step-by-step code examples for integrating cognitive processes
- Quick Reference - Cheat sheets and decision trees for developers
Documentation Structure
This system's documentation is organized by content type following the Diátaxis framework:
Tutorials
Step-by-step guides for learning cognitive process modeling:
- Coming soon: Getting Started with Cognitive Process Modeling
How-to Guides
Task-focused instructions for implementation:
- Implementation Guide - Complete implementation guide with code examples
Reference
Precise, factual information:
- Quick Reference - Quick lookup tables, code snippets, and decision trees
Explanation
Deep context and architecture:
- Cognitive Processes Research - Complete research document with all 12 stages
- Visual Diagrams - Mermaid diagrams and flow charts
The 12 Cognitive Stages
- Sensory Reception (0-50ms) - Raw input encoding
- Perceptual Processing (50-150ms) - Feature extraction
- Attention & Filtering (100-200ms) - Focus selection
- Memory Access (150-300ms) - Context retrieval
- Emotional Processing (100-400ms) - Emotional appraisal
- Interpretation (200-500ms) - Meaning-making
- Decision Strategy (300-600ms) - Fast vs slow choice
- Evidence Accumulation (400ms+) - Reasoning
- Response Planning (500ms-2s) - Content formulation
- Self-Monitoring (200-500ms) - Validation
- Response Execution (Varies) - Output delivery
- Feedback & Learning (Ongoing) - Improvement
Dual Process Theory
System 1 (Fast/Intuitive)
- Speed: ~300ms
- Characteristics: Automatic, pattern-based, emotional
- Use When: High confidence, low ambiguity, familiar patterns
System 2 (Slow/Deliberate)
- Speed: 500ms - several seconds
- Characteristics: Analytical, reasoning-based, conscious
- Use When: Low confidence, high ambiguity, complex reasoning needed
Quick Links
- Research Document: Explanation/Cognitive-Processes-Research.md
- Visual Diagrams: Explanation/Diagrams.md
- Implementation Guide: How-to/Implementation-Guide.md
- Quick Reference: Reference/Quick-Reference.md
Related Documentation
- Prompt System - Current prompt system architecture
- Memory System - Memory and context systems
- Observer System - Meta-consciousness system
- 00-OVERVIEW.md - Complete system overview
Implementation Status
- Phase 1: Foundation - Implemented (fast Perception + Salience)
- Phase 2: Dual Processing - Partial (protocol-level gating via
cognitiveDepth) - Phase 3: Advanced Features - Implemented (optional self-monitoring rewrite pass)
- Phase 4: Integration - Implemented (wired into
backend/src/services/aso.service.ts)
Next Steps
- Review the research documentation
- Prioritize implementation phases
- Design prompt templates for each cognitive stage
- Create service architecture
- Implement and test
Document Version: 1.0
Last Updated: 2024
Status: Active Research