---
title: Cognitive Concepts Index
type: index
status: stable
created: 2024-02-07
tags:
  - concepts
  - cognitive
  - index
semantic_relations:
  - type: organizes
    links:
      - [[cognitive_theory]]
      - [[implementation_concepts]]
---

# Cognitive Concepts Index

## Theoretical Foundations

### Active Inference
- [[concepts/active_inference/theory|Active Inference Theory]]
- [[concepts/active_inference/free_energy|Free Energy Principle]]
- [[concepts/active_inference/variational|Variational Inference]]
- [[concepts/active_inference/belief_updating|Belief Updating]]
- [[concepts/active_inference/policy_selection|Policy Selection]]

### Predictive Processing
- [[concepts/predictive/hierarchical|Hierarchical Processing]]
- [[concepts/predictive/precision|Precision Weighting]]
- [[concepts/predictive/prediction_error|Prediction Error]]
- [[concepts/predictive/generative_models|Generative Models]]

### Information Theory
- [[concepts/information/entropy|Entropy]]
- [[concepts/information/kl_divergence|KL Divergence]]
- [[concepts/information/mutual_information|Mutual Information]]
- [[concepts/information/information_geometry|Information Geometry]]

## Implementation Concepts

### Agent Architecture
- [[concepts/architecture/belief_states|Belief States]]
- [[concepts/architecture/policy_space|Policy Space]]
- [[concepts/architecture/observation_model|Observation Model]]
- [[concepts/architecture/transition_model|Transition Model]]

### Learning Mechanisms
- [[concepts/learning/parameter_learning|Parameter Learning]]
- [[concepts/learning/structure_learning|Structure Learning]]
- [[concepts/learning/meta_learning|Meta-Learning]]
- [[concepts/learning/active_learning|Active Learning]]

### System Integration
- [[concepts/integration/perception|Perception Integration]]
- [[concepts/integration/action|Action Integration]]
- [[concepts/integration/memory|Memory Integration]]
- [[concepts/integration/attention|Attention Integration]]

## Advanced Concepts

### Hierarchical Processing
- [[concepts/hierarchical/temporal|Temporal Hierarchies]]
- [[concepts/hierarchical/spatial|Spatial Hierarchies]]
- [[concepts/hierarchical/conceptual|Conceptual Hierarchies]]
- [[concepts/hierarchical/abstraction|Abstraction Levels]]

### Multi-Agent Systems
- [[concepts/multi_agent/coordination|Agent Coordination]]
- [[concepts/multi_agent/communication|Agent Communication]]
- [[concepts/multi_agent/collective|Collective Behavior]]
- [[concepts/multi_agent/emergence|Emergent Behavior]]

### Complex Systems
- [[concepts/complex/self_organization|Self-Organization]]
- [[concepts/complex/emergence|Emergence]]
- [[concepts/complex/adaptation|Adaptation]]
- [[concepts/complex/criticality|Criticality]]

## Mathematical Foundations

### Probability Theory
- [[concepts/probability/bayesian|Bayesian Inference]]
- [[concepts/probability/distributions|Probability Distributions]]
- [[concepts/probability/graphical_models|Graphical Models]]
- [[concepts/probability/sampling|Sampling Methods]]

### Optimization
- [[concepts/optimization/variational|Variational Methods]]
- [[concepts/optimization/gradient|Gradient Methods]]
- [[concepts/optimization/stochastic|Stochastic Methods]]
- [[concepts/optimization/constrained|Constrained Optimization]]

### Dynamical Systems
- [[concepts/dynamics/continuous|Continuous Dynamics]]
- [[concepts/dynamics/discrete|Discrete Dynamics]]
- [[concepts/dynamics/stochastic|Stochastic Dynamics]]
- [[concepts/dynamics/chaos|Chaos Theory]]

## Implementation Examples

### Basic Examples
```python
# Basic active inference agent
class ActiveInferenceAgent:
    def __init__(self):
        self.beliefs = initialize_beliefs()
        self.model = create_generative_model()
        
    def update(self, observation):
        # Update beliefs using variational inference
        self.beliefs = update_beliefs(self.beliefs, observation)
        
        # Select action using expected free energy
        action = select_action(self.beliefs)
        return action
```

### Advanced Examples
```python
# Hierarchical active inference
class HierarchicalAgent:
    def __init__(self, levels):
        self.levels = [
            ActiveInferenceAgent() 
            for _ in range(levels)
        ]
        
    def update(self, observation):
        # Bottom-up message passing
        for level in self.levels:
            prediction = level.predict()
            observation = level.update(observation)
            
        # Top-down action selection
        action = self.levels[-1].select_action()
        return action
```

## Related Resources

### Documentation
- [[docs/guides/concept_guides|Concept Guides]]
- [[docs/api/concept_api|Concept API]]
- [[docs/examples/concept_examples|Concept Examples]]

### Knowledge Base
- [[knowledge_base/cognitive/concepts|Cognitive Concepts]]
- [[knowledge_base/mathematics/concepts|Mathematical Concepts]]
- [[knowledge_base/systems/concepts|Systems Concepts]]

### Learning Resources
- [[learning_paths/concepts|Concept Learning Path]]
- [[tutorials/concepts|Concept Tutorials]]
- [[guides/concepts/best_practices|Concept Best Practices]]