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155 строки
5.0 KiB
Markdown
155 строки
5.0 KiB
Markdown
---
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title: Cognitive Concepts Index
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type: index
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status: stable
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created: 2024-02-07
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tags:
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- concepts
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- cognitive
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- index
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semantic_relations:
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- type: organizes
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links:
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- [[cognitive_theory]]
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- [[implementation_concepts]]
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---
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# Cognitive Concepts Index
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## Theoretical Foundations
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### Active Inference
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- [[concepts/active_inference/theory|Active Inference Theory]]
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- [[concepts/active_inference/free_energy|Free Energy Principle]]
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- [[concepts/active_inference/variational|Variational Inference]]
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- [[concepts/active_inference/belief_updating|Belief Updating]]
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- [[concepts/active_inference/policy_selection|Policy Selection]]
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### Predictive Processing
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- [[concepts/predictive/hierarchical|Hierarchical Processing]]
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- [[concepts/predictive/precision|Precision Weighting]]
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- [[concepts/predictive/prediction_error|Prediction Error]]
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- [[concepts/predictive/generative_models|Generative Models]]
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### Information Theory
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- [[concepts/information/entropy|Entropy]]
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- [[concepts/information/kl_divergence|KL Divergence]]
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- [[concepts/information/mutual_information|Mutual Information]]
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- [[concepts/information/information_geometry|Information Geometry]]
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## Implementation Concepts
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### Agent Architecture
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- [[concepts/architecture/belief_states|Belief States]]
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- [[concepts/architecture/policy_space|Policy Space]]
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- [[concepts/architecture/observation_model|Observation Model]]
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- [[concepts/architecture/transition_model|Transition Model]]
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### Learning Mechanisms
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- [[concepts/learning/parameter_learning|Parameter Learning]]
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- [[concepts/learning/structure_learning|Structure Learning]]
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- [[concepts/learning/meta_learning|Meta-Learning]]
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- [[concepts/learning/active_learning|Active Learning]]
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### System Integration
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- [[concepts/integration/perception|Perception Integration]]
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- [[concepts/integration/action|Action Integration]]
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- [[concepts/integration/memory|Memory Integration]]
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- [[concepts/integration/attention|Attention Integration]]
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## Advanced Concepts
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### Hierarchical Processing
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- [[concepts/hierarchical/temporal|Temporal Hierarchies]]
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- [[concepts/hierarchical/spatial|Spatial Hierarchies]]
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- [[concepts/hierarchical/conceptual|Conceptual Hierarchies]]
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- [[concepts/hierarchical/abstraction|Abstraction Levels]]
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### Multi-Agent Systems
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- [[concepts/multi_agent/coordination|Agent Coordination]]
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- [[concepts/multi_agent/communication|Agent Communication]]
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- [[concepts/multi_agent/collective|Collective Behavior]]
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- [[concepts/multi_agent/emergence|Emergent Behavior]]
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### Complex Systems
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- [[concepts/complex/self_organization|Self-Organization]]
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- [[concepts/complex/emergence|Emergence]]
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- [[concepts/complex/adaptation|Adaptation]]
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- [[concepts/complex/criticality|Criticality]]
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## Mathematical Foundations
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### Probability Theory
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- [[concepts/probability/bayesian|Bayesian Inference]]
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- [[concepts/probability/distributions|Probability Distributions]]
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- [[concepts/probability/graphical_models|Graphical Models]]
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- [[concepts/probability/sampling|Sampling Methods]]
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### Optimization
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- [[concepts/optimization/variational|Variational Methods]]
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- [[concepts/optimization/gradient|Gradient Methods]]
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- [[concepts/optimization/stochastic|Stochastic Methods]]
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- [[concepts/optimization/constrained|Constrained Optimization]]
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### Dynamical Systems
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- [[concepts/dynamics/continuous|Continuous Dynamics]]
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- [[concepts/dynamics/discrete|Discrete Dynamics]]
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- [[concepts/dynamics/stochastic|Stochastic Dynamics]]
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- [[concepts/dynamics/chaos|Chaos Theory]]
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## Implementation Examples
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### Basic Examples
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```python
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# Basic active inference agent
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class ActiveInferenceAgent:
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def __init__(self):
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self.beliefs = initialize_beliefs()
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self.model = create_generative_model()
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def update(self, observation):
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# Update beliefs using variational inference
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self.beliefs = update_beliefs(self.beliefs, observation)
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# Select action using expected free energy
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action = select_action(self.beliefs)
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return action
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```
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### Advanced Examples
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```python
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# Hierarchical active inference
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class HierarchicalAgent:
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def __init__(self, levels):
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self.levels = [
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ActiveInferenceAgent()
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for _ in range(levels)
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]
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def update(self, observation):
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# Bottom-up message passing
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for level in self.levels:
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prediction = level.predict()
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observation = level.update(observation)
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# Top-down action selection
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action = self.levels[-1].select_action()
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return action
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```
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## Related Resources
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### Documentation
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- [[docs/guides/concept_guides|Concept Guides]]
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- [[docs/api/concept_api|Concept API]]
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- [[docs/examples/concept_examples|Concept Examples]]
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### Knowledge Base
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- [[knowledge_base/cognitive/concepts|Cognitive Concepts]]
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- [[knowledge_base/mathematics/concepts|Mathematical Concepts]]
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- [[knowledge_base/systems/concepts|Systems Concepts]]
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### Learning Resources
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- [[learning_paths/concepts|Concept Learning Path]]
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- [[tutorials/concepts|Concept Tutorials]]
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- [[guides/concepts/best_practices|Concept Best Practices]] |