# Project Structure

## Overview

This document outlines the comprehensive organization of the cognitive modeling framework, detailing the purpose and relationships between different components.

## Core Directories

### 📁 knowledge_base/
Core knowledge organization and theoretical foundations

#### Cognitive Domain
- `cognitive/` - Core cognitive concepts
  - `active_inference/` - Active Inference framework
  - `belief_updating/` - Belief update mechanisms
  - `policy_selection/` - Action selection algorithms
  - `free_energy/` - Free Energy calculations
  - `predictive_processing/` - Predictive processing theory

#### Mathematical Domain
- `mathematics/` - Mathematical foundations
  - `probability/` - Probability theory
  - `information_theory/` - Information theoretic concepts
  - `optimization/` - Optimization methods
  - `dynamical_systems/` - System dynamics

#### Implementation Domain
- `implementations/` - Concrete examples
  - `navigation/` - Navigation tasks
  - `foraging/` - Resource foraging
  - `coordination/` - Multi-agent coordination
  - `learning/` - Learning scenarios

### 📁 src/
Source code implementation

#### Core Components
- `models/` - Core modeling components
  - `active_inference/` - Active Inference implementation
    - `generative_model.py`
    - `belief_updater.py`
    - `policy_selector.py`
  - `state_estimation/` - State estimation tools
  - `optimization/` - Optimization algorithms

#### Utility Functions
- `utils/` - Utility functions
  - `visualization/` - Visualization tools
    - `state_space.py`
    - `belief_plots.py`
    - `network_viz.py`
  - `validation/` - Validation utilities
    - `matrix_validation.py`
    - `model_checks.py`
  - `data_processing/` - Data handling

#### Analysis Tools
- `analysis/` - Analysis tools
  - `metrics/` - Performance metrics
  - `network_analysis/` - Network analysis
  - `simulations/` - Simulation frameworks

### 📁 tests/
Comprehensive test suite

#### Test Categories
- `unit/` - Unit tests
  - `test_matrix_ops.py`
  - `test_belief_updates.py`
  - `test_policy_selection.py`
- `integration/` - Integration tests
  - `test_agent_environment.py`
  - `test_learning_scenarios.py`
- `visualization/` - Visualization tests
  - `test_state_plots.py`
  - `test_network_viz.py`

### 📁 docs/
Project documentation

#### Documentation Types
- `theory/` - Theoretical foundations
  - `active_inference.md`
  - `free_energy.md`
  - `predictive_processing.md`
- `implementation/` - Implementation details
  - `api_reference.md`
  - `class_documentation.md`
  - `function_specifications.md`
- `examples/` - Usage examples
  - `quickstart.md`
  - `tutorials/`
  - `case_studies/`

### 📁 templates/
Reusable templates and patterns

#### Template Categories
- `concepts/` - Concept templates
  - `cognitive_template.md`
  - `mathematical_template.md`
  - `implementation_template.md`
- `documentation/` - Documentation templates
  - `api_template.md`
  - `example_template.md`
  - `tutorial_template.md`

## File Organization

### Naming Conventions
- Use lowercase with underscores
- Include category prefixes
- Be descriptive and concise

### File Structure
- Include header metadata
- Follow consistent organization
- Maintain clear dependencies

### Version Control
- Use meaningful commits
- Group related changes
- Track dependencies

## Development Workflow

### 1. Knowledge Development
1. Create concept documentation
2. Establish relationships
3. Validate theoretical consistency
4. Update dependencies

### 2. Implementation
1. Write core functionality
2. Add unit tests
3. Create integration tests
4. Document API

### 3. Validation
1. Run test suite
2. Check coverage
3. Validate relationships
4. Review documentation

### 4. Deployment
1. Update version
2. Generate documentation
3. Create release notes
4. Deploy changes

## Quality Assurance

### Documentation Standards
- Complete API documentation
- Clear usage examples
- Comprehensive guides
- Up-to-date references

### Testing Requirements
- High test coverage
- Integration testing
- Property-based tests
- Performance benchmarks

### Code Quality
- Follow style guide
- Use type hints
- Write clear comments
- Maintain modularity

## References

### Documentation
- Project style guide
- API documentation
- Testing guide
- Contribution guide

### Dependencies
- requirements.txt
- setup.py
- environment.yml
- Dockerfile