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README.md
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# cognitive
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# Cognitive Ecosystem Modeling Framework
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A comprehensive framework for modeling cognitive ecosystems using [[active_inference|Active Inference]], integrated with [[obsidian_linking|Obsidian]] for knowledge management.
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## Overview
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This project combines cognitive modeling with knowledge management to create a powerful framework for:
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- Modeling agent behaviors using [[active_inference|Active Inference]]
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- Managing complex [[knowledge_organization|knowledge structures]]
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- Visualizing and analyzing [[cognitive_phenomena|cognitive networks]]
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- Simulating multi-agent interactions
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## Project Structure
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||||
|
||||
See [[ai_folder_structure]] for comprehensive directory organization.
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```
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📁 templates/ # Template definitions
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├── node_templates/ # Base templates for cognitive nodes
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│ ├── agent_template.md # See [[ai_concept_template]]
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│ ├── belief_template.md
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│ └── ...
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│
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📁 knowledge_base/ # Knowledge structure
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├── cognitive/ # Core cognitive concepts
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├── agents/ # Agent definitions
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├── beliefs/ # Belief networks
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└── ...
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📁 src/ # Source code
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├── models/ # Core modeling components
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├── utils/ # Utility functions
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└── analysis/ # Analysis tools
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📁 docs/ # Documentation (See [[documentation_standards]])
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📁 tests/ # Test suite (See [[testing_guide]])
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📁 data/ # Data storage
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```
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## Features
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### Knowledge Management
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- [[obsidian_linking|Obsidian-compatible markdown files]]
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- [[linking_completeness|Bidirectional linking]]
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- [[ai_concept_template|Template-based node creation]]
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- [[ai_validation_framework|Automated relationship tracking]]
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### Cognitive Modeling
|
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- [[active_inference|Active Inference implementation]]
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- [[belief_updating|Belief updating mechanisms]]
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- [[action_selection|Policy selection algorithms]]
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- [[predictive_processing|State estimation tools]]
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|
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### Analysis & Visualization
|
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- [[network_analysis|Network analysis]]
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- [[quality_metrics|Performance metrics]]
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- [[visualization_tools|Interactive visualizations]]
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- [[simulation_studies|Simulation frameworks]]
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## Knowledge Integration Architecture
|
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|
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### Bidirectional Knowledge Graph
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The framework leverages [[obsidian_linking|Obsidian's linking capabilities]] to create a living knowledge graph that:
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- Enforces [[validation_framework|mathematical and theoretical consistency]]
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- Enables [[ai_validation_framework|automated validation]] of relationships
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- Supports [[machine_readability|dynamic discovery]] of dependencies
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- Facilitates [[research_education|learning through exploration]]
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|
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#### Link Types and Semantics
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See [[linking_completeness]] for comprehensive linking patterns.
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1. Theoretical Dependencies
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```markdown
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[[measure_theory]] → [[probability_theory]] → [[stochastic_processes]]
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```
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- Enforces prerequisite knowledge
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- Validates theoretical foundations
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- Ensures consistent notation
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2. Implementation Dependencies
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```markdown
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[[active_inference]] → [[belief_updating]] → [[action_selection]]
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```
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- Tracks computational requirements
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- Maintains implementation consistency
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- Documents design decisions
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3. Validation Links
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```markdown
|
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[[testing_guide]] → [[validation_framework]] → [[quality_metrics]]
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```
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- Ensures rigorous testing
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- Maintains quality standards
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- Documents validation procedures
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### Probabilistic Programming Integration
|
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|
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#### Graph Structure Mapping
|
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The repository's link structure directly maps to probabilistic graphical models:
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```python
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# Example: Converting knowledge links to Bayesian Graph
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def build_bayesian_graph(knowledge_base: Path) -> BayesianNetwork:
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"""Convert knowledge base links to Bayesian Network.
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See [[ai_semantic_processing]] for details.
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"""
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graph = BayesianNetwork()
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# Extract links and dependencies
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for file in knowledge_base.glob('**/*.md'):
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links = extract_links(file)
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nodes = create_nodes(links)
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edges = create_edges(links)
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# Add to graph with conditional probabilities
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graph.add_nodes(nodes)
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graph.add_edges(edges)
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return graph
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```
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#### Implementation Patterns
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See [[package_documentation]] for detailed implementation guidelines.
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1. Direct Specification
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```yaml
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# In matrix_specification.md
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matrix:
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type: observation
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dimensions: [num_states, num_observations]
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distribution: categorical
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parameters:
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prior: dirichlet
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concentration: [1.0, ..., 1.0]
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```
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2. Probabilistic Annotations
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```python
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@probabilistic_model
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class ObservationModel:
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"""Implementation with probabilistic annotations.
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See [[predictive_processing]] for theoretical background.
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"""
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def __init__(self):
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self.A = PyroMatrix(dims=['states', 'obs'])
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def forward(self, state):
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return pyro.sample('obs',
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dist.Categorical(self.A[state]))
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```
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3. Inference Specifications
|
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```yaml
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inference:
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method: variational
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guide: mean_field
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optimizer: adam
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parameters:
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learning_rate: 0.01
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num_particles: 10
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```
|
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|
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### Knowledge Base Integration
|
||||
|
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#### Automated Validation
|
||||
```python
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def validate_knowledge_base():
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"""Validate theoretical consistency.
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See [[ai_validation_framework]] for details.
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"""
|
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# Check link consistency
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validate_theoretical_dependencies()
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# Verify probabilistic specifications
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validate_probability_constraints()
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# Test implementation coherence
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validate_implementation_patterns()
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```
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#### Learning Pathways
|
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See [[research_education]] for comprehensive learning integration.
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|
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- **Theory**: Follow theoretical dependency chains
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```markdown
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[[measure_theory]] → [[probability_theory]] → [[active_inference]]
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```
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||||
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- **Implementation**: Track implementation requirements
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||||
```markdown
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[[matrix_design]] → [[numerical_methods]] → [[optimization]]
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```
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- **Validation**: Ensure testing coverage
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||||
```markdown
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[[unit_tests]] → [[integration_tests]] → [[system_validation]]
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||||
```
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||||
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### Meta-Programming Capabilities
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#### Code Generation
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```python
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def generate_model_code(spec_file: Path) -> str:
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"""Generate implementation from specifications.
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See [[ai_documentation_style]] for code generation patterns.
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"""
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# Parse markdown specifications
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spec = parse_markdown_spec(spec_file)
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# Extract probabilistic model
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model = extract_probabilistic_model(spec)
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# Generate implementation
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return generate_implementation(model)
|
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```
|
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|
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#### Validation Rules
|
||||
```python
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def check_probabilistic_consistency():
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"""Verify probabilistic consistency.
|
||||
See [[validation_framework]] for validation rules.
|
||||
"""
|
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# Check matrix constraints
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verify_stochastic_matrices()
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# Validate probability measures
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verify_measure_consistency()
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|
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# Check inference specifications
|
||||
verify_inference_methods()
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```
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### Benefits
|
||||
|
||||
1. **Theoretical Consistency**
|
||||
- [[ai_validation_framework|Automated validation]] of mathematical relationships
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||||
- Enforcement of probabilistic constraints
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||||
- Verification of implementation patterns
|
||||
|
||||
2. **Learning Support**
|
||||
- [[research_education|Guided exploration]] of concepts
|
||||
- Clear dependency tracking
|
||||
- Interactive knowledge discovery
|
||||
|
||||
3. **Implementation Quality**
|
||||
- [[ai_documentation_style|Automated code generation]]
|
||||
- Consistent design patterns
|
||||
- [[testing_guide|Rigorous testing framework]]
|
||||
|
||||
4. **Documentation Integration**
|
||||
- [[documentation_standards|Living documentation]]
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||||
- [[package_documentation|Executable specifications]]
|
||||
- [[ai_validation_framework|Automated validation]]
|
||||
|
||||
## Getting Started
|
||||
|
||||
1. **Setup Environment**
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||||
```bash
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python -m venv venv
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source venv/bin/activate # or `venv\Scripts\activate` on Windows
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pip install -r requirements.txt
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```
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2. **Configure Project**
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- Edit `config.yaml` for project settings
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- Customize templates in `templates/`
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- Set up [[obsidian_linking|Obsidian vault integration]]
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3. **Create Cognitive Models**
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- Use [[ai_concept_template|templates]] to define agents
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- Configure belief networks
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- Set up observation spaces
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- Define action policies
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4. **Run Simulations**
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- Execute model simulations
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- Analyze results
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- Visualize networks
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|
||||
## Testing
|
||||
|
||||
See [[testing_guide]] for comprehensive testing documentation.
|
||||
|
||||
### Running Tests
|
||||
```bash
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# Run all tests with verbose output
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python -m pytest -v
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|
||||
# Run specific test file
|
||||
python -m pytest tests/test_matrix_ops.py -v
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|
||||
# Run tests with coverage report
|
||||
python -m pytest --cov=src
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||||
```
|
||||
|
||||
### Test Organization
|
||||
- `tests/test_matrix_ops.py`: Matrix operation tests
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- `tests/test_visualization.py`: Visualization component tests
|
||||
- `tests/conftest.py`: Shared test fixtures and configuration
|
||||
|
||||
## Development
|
||||
|
||||
### Contributing
|
||||
See [[contribution_guide]] for detailed contribution guidelines.
|
||||
|
||||
### Documentation
|
||||
- [[api_documentation|API Documentation]]
|
||||
- [[documentation_guide|User Guide]]
|
||||
- [[example_writing|Examples]]
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||||
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||||
## License
|
||||
|
||||
This project is licensed under the MIT License - see the LICENSE file for details.
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## Acknowledgments
|
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|
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- Active Inference research community
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- Obsidian development team
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- Contributors and maintainers
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||||
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|
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|
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146
project_structure.md
Обычный файл
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project_structure.md
Обычный файл
@ -0,0 +1,146 @@
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# Project Structure
|
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|
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## Core Directories
|
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|
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### 📁 templates/
|
||||
- `node_templates/` - Base templates for different types of cognitive nodes (See [[ai_concept_template]])
|
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- `agent_template.md` - Template for [[active_inference]] agent definitions
|
||||
- `belief_template.md` - Template for [[belief_updating]] structures
|
||||
- `goal_template.md` - Template for goal hierarchies and optimization
|
||||
- `action_template.md` - Template for [[action_selection]] definitions
|
||||
- `observation_template.md` - Template for [[predictive_processing]] patterns
|
||||
- `relationship_template.md` - Template for [[linking_completeness|node relationships]]
|
||||
|
||||
### 📁 knowledge_base/
|
||||
- `cognitive/` - Core cognitive concepts (See [[cognitive_phenomena]])
|
||||
- [[active_inference]] - Active Inference framework
|
||||
- [[free_energy_principle]] - Free Energy Principle
|
||||
- [[predictive_processing]] - Predictive Processing theory
|
||||
- `agents/` - Agent definitions and states
|
||||
- `beliefs/` - Belief networks and structures
|
||||
- `goals/` - Goal hierarchies and definitions
|
||||
- `actions/` - Action repertoires and policies
|
||||
- `observations/` - Observation patterns and histories
|
||||
- `relationships/` - Inter-node relationships and dynamics
|
||||
|
||||
### 📁 src/
|
||||
- `models/` - Core modeling components
|
||||
- `active_inference/` - [[active_inference|Active Inference]] implementation
|
||||
- `belief_updating/` - [[belief_updating|Belief update mechanisms]]
|
||||
- `policy_selection/` - [[action_selection|Policy selection algorithms]]
|
||||
- `state_estimation/` - State estimation tools
|
||||
- `utils/` - Utility functions and helpers
|
||||
- `visualization/` - [[visualization_tools|Visualization tools]]
|
||||
- `data_processing/` - Data processing utilities
|
||||
- `obsidian_integration/` - [[obsidian_linking|Obsidian integration tools]]
|
||||
- `analysis/` - Analysis tools and scripts
|
||||
- `network_analysis/` - Network analysis tools
|
||||
- `metrics/` - Performance and behavior metrics
|
||||
- `simulations/` - Simulation frameworks
|
||||
|
||||
### 📁 docs/
|
||||
See [[documentation_standards]] for comprehensive documentation guidelines
|
||||
|
||||
#### Core Documentation
|
||||
- `api/` - API Reference Documentation
|
||||
- [[api_documentation]] - API documentation guidelines
|
||||
- [[api_reference]] - Complete API reference
|
||||
- [[api_versioning]] - API versioning guidelines
|
||||
- [[api_examples]] - API usage examples
|
||||
|
||||
#### Conceptual Documentation
|
||||
- `concepts/` - Core Concepts and Theory
|
||||
- [[machine_readability]] - Machine processing principles
|
||||
- [[plain_text_benefits]] - Benefits of plain text
|
||||
- [[research_education]] - Research and education integration
|
||||
- [[cognitive_phenomena]] - Cognitive phenomena catalog
|
||||
- [[theoretical_foundations]] - Theoretical background
|
||||
|
||||
#### Implementation Guides
|
||||
- `guides/` - Usage Guides and Tutorials
|
||||
- [[ai_documentation_style]] - Documentation style guide
|
||||
- [[ai_file_organization]] - File organization guide
|
||||
- [[ai_folder_structure]] - Directory structure guide
|
||||
- [[ai_semantic_processing]] - Semantic processing guide
|
||||
- [[ai_validation_framework]] - Validation framework
|
||||
- [[linking_completeness]] - Link completeness guide
|
||||
- [[linking_analysis]] - Link analysis guide
|
||||
- [[linking_validation]] - Link validation guide
|
||||
- [[obsidian_linking]] - Obsidian integration guide
|
||||
- [[package_documentation]] - Package documentation guide
|
||||
|
||||
#### Example Documentation
|
||||
- `examples/` - Example Implementations
|
||||
- [[example_writing]] - Example writing guide
|
||||
- [[quickstart_example]] - Quick start tutorial
|
||||
- [[active_inference_example]] - Active inference examples
|
||||
- [[belief_updating_example]] - Belief updating examples
|
||||
- [[integration_examples]] - Integration examples
|
||||
- [[validation_examples]] - Validation examples
|
||||
|
||||
#### Template Documentation
|
||||
- `templates/` - Documentation Templates
|
||||
- [[package_component]] - Package component template
|
||||
- [[ai_concept_template]] - AI concept template
|
||||
- [[linking_template]] - Linking template
|
||||
- [[validation_template]] - Validation template
|
||||
- [[example_template]] - Example template
|
||||
- [[guide_template]] - Guide template
|
||||
|
||||
#### Tool Documentation
|
||||
- `tools/` - Development Tools
|
||||
- [[documentation_tools]] - Documentation tooling
|
||||
- [[validation_tools]] - Validation tools
|
||||
- [[visualization_tools]] - Visualization tools
|
||||
- [[analysis_tools]] - Analysis tools
|
||||
- [[generation_tools]] - Code generation tools
|
||||
|
||||
#### Research Documentation
|
||||
- `research/` - Research Documentation
|
||||
- [[experiment_documentation]] - Experiment documentation
|
||||
- [[result_analysis]] - Result analysis
|
||||
- [[literature_review]] - Literature review
|
||||
- [[theoretical_development]] - Theory development
|
||||
|
||||
### 📁 tests/
|
||||
- Unit tests and integration tests (See [[testing_guide]])
|
||||
- `test_matrix_ops.py` - Matrix operation tests
|
||||
- `test_visualization.py` - Visualization tests
|
||||
- `conftest.py` - Shared test fixtures
|
||||
|
||||
### 📁 data/
|
||||
- `raw/` - Raw data storage
|
||||
- `processed/` - Processed data
|
||||
- `results/` - Analysis results
|
||||
|
||||
## Key Files
|
||||
|
||||
- `requirements.txt` - Python dependencies
|
||||
- `setup.py` - Package setup
|
||||
- `README.md` - Project documentation (See [[documentation_standards]])
|
||||
- `CONTRIBUTING.md` - [[contribution_guide|Contribution guidelines]]
|
||||
- `.gitignore` - [[git_workflow|Git ignore rules]]
|
||||
- `config.yaml` - Configuration settings
|
||||
|
||||
## Documentation Integration
|
||||
|
||||
### Knowledge Graph Structure
|
||||
The project follows a [[linking_completeness|comprehensive linking structure]] that ensures:
|
||||
- Bidirectional relationships between components
|
||||
- Clear dependency chains
|
||||
- Traceable implementations
|
||||
- Validated connections
|
||||
|
||||
### Validation Framework
|
||||
See [[ai_validation_framework]] for details on:
|
||||
- Link validation
|
||||
- Documentation completeness
|
||||
- Quality metrics
|
||||
- Automated checks
|
||||
|
||||
### Best Practices
|
||||
Follow these guides for development:
|
||||
- [[ai_documentation_style]] - Documentation style guide
|
||||
- [[ai_file_organization]] - File organization patterns
|
||||
- [[ai_folder_structure]] - Directory structure guidelines
|
||||
- [[ai_semantic_processing]] - Semantic processing integration
|
||||
47
requirements.txt
Обычный файл
47
requirements.txt
Обычный файл
@ -0,0 +1,47 @@
|
||||
# Core Scientific Computing
|
||||
numpy>=1.21.0
|
||||
scipy>=1.7.0
|
||||
pandas>=1.3.0
|
||||
scikit-learn>=0.24.0
|
||||
|
||||
# Deep Learning (Optional)
|
||||
torch>=1.9.0
|
||||
tensorflow>=2.6.0
|
||||
|
||||
# Probabilistic Programming
|
||||
pymc3>=3.11.0
|
||||
pomegranate>=0.14.0
|
||||
|
||||
# Visualization
|
||||
matplotlib>=3.4.0
|
||||
seaborn>=0.11.0
|
||||
networkx>=2.6.0
|
||||
plotly>=5.1.0
|
||||
|
||||
# Data Processing
|
||||
pyyaml>=5.4.0
|
||||
jinja2>=3.0.0
|
||||
markdown>=3.3.0
|
||||
|
||||
# Testing and Development
|
||||
pytest>=6.2.0
|
||||
black>=21.6b0
|
||||
flake8>=3.9.0
|
||||
mypy>=0.910
|
||||
|
||||
# Documentation
|
||||
sphinx>=4.0.0
|
||||
sphinx-rtd-theme>=0.5.0
|
||||
|
||||
# Utilities
|
||||
tqdm>=4.61.0
|
||||
click>=8.0.0
|
||||
python-dotenv>=0.19.0
|
||||
|
||||
# Optimization
|
||||
optuna>=2.9.0
|
||||
hyperopt>=0.2.5
|
||||
|
||||
# Monitoring and Logging
|
||||
wandb>=0.12.0
|
||||
mlflow>=1.19.0
|
||||
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