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			199 строки
		
	
	
		
			5.6 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
| ---
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| title: Examples 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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|   - examples
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|   - implementation
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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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|       - [[implementation_examples]]
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|       - [[usage_examples]]
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| ---
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| 
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| # Examples Index
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| 
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| ## Core Examples
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| 
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| ### Active Inference Examples
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| - [[examples/active_inference/basic|Basic Active Inference]]
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| - [[examples/active_inference/hierarchical|Hierarchical Active Inference]]
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| - [[examples/active_inference/multi_agent|Multi-Agent Active Inference]]
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| 
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| ### POMDP Examples
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| - [[examples/pomdp/basic|Basic POMDP]]
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| - [[examples/pomdp/belief_updating|Belief Updating]]
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| - [[examples/pomdp/policy_selection|Policy Selection]]
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| 
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| ### Swarm Intelligence Examples
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| - [[examples/swarm/ant_colony|Ant Colony Simulation]]
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| - [[examples/swarm/particle_swarm|Particle Swarm]]
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| - [[examples/swarm/flocking|Flocking Behavior]]
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| 
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| ## Implementation Examples
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| 
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| ### Agent Implementation
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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, config):
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|         self.beliefs = initialize_beliefs()
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|         self.model = create_generative_model()
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|         
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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(
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|             self.beliefs, observation, self.model
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|         )
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|         
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|         # Select action using expected free energy
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|         action = select_action(self.beliefs, self.model)
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|         return action
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| ```
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| 
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| ### Environment Implementation
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| ```python
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| # Basic environment setup
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| class Environment:
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|     def __init__(self, config):
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|         self.state = initialize_state()
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|         self.agents = create_agents()
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|         
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|     def step(self, actions):
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|         # Update environment state
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|         self.state = update_state(self.state, actions)
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|         
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|         # Generate observations
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|         observations = generate_observations(self.state)
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|         return observations
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| ```
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| 
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| ### Simulation Implementation
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| ```python
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| # Basic simulation loop
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| def run_simulation(config):
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|     env = Environment(config)
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|     agent = ActiveInferenceAgent(config)
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|     
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|     for step in range(config.max_steps):
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|         # Agent-environment interaction
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|         observation = env.get_observation()
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|         action = agent.update(observation)
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|         env.step(action)
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| ```
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| 
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| ## Advanced Examples
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| 
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| ### Hierarchical Systems
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| - [[examples/hierarchical/perception|Hierarchical Perception]]
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| - [[examples/hierarchical/control|Hierarchical Control]]
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| - [[examples/hierarchical/learning|Hierarchical Learning]]
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| 
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| ### Multi-Agent Systems
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| - [[examples/multi_agent/coordination|Agent Coordination]]
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| - [[examples/multi_agent/communication|Agent Communication]]
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| - [[examples/multi_agent/learning|Collective Learning]]
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| 
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| ### Complex Systems
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| - [[examples/complex/emergence|Emergence Patterns]]
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| - [[examples/complex/adaptation|System Adaptation]]
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| - [[examples/complex/evolution|System Evolution]]
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| 
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| ## Application Examples
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| 
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| ### Robotics Applications
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| - [[examples/robotics/control|Robot Control]]
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| - [[examples/robotics/navigation|Robot Navigation]]
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| - [[examples/robotics/manipulation|Robot Manipulation]]
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| 
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| ### Cognitive Applications
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| - [[examples/cognitive/learning|Learning Systems]]
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| - [[examples/cognitive/memory|Memory Systems]]
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| - [[examples/cognitive/attention|Attention Systems]]
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| 
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| ### Biological Applications
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| - [[examples/biological/neural|Neural Systems]]
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| - [[examples/biological/collective|Collective Behavior]]
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| - [[examples/biological/adaptation|Adaptive Behavior]]
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| 
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| ## Integration Examples
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| 
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| ### Framework Integration
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| - [[examples/integration/pytorch|PyTorch Integration]]
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| - [[examples/integration/tensorflow|TensorFlow Integration]]
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| - [[examples/integration/jax|JAX Integration]]
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| 
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| ### Tool Integration
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| - [[examples/tools/visualization|Visualization Tools]]
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| - [[examples/tools/analysis|Analysis Tools]]
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| - [[examples/tools/profiling|Profiling Tools]]
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| 
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| ### System Integration
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| - [[examples/systems/environment|Environment Integration]]
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| - [[examples/systems/hardware|Hardware Integration]]
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| - [[examples/systems/distributed|Distributed Systems]]
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| 
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| ## Testing Examples
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| 
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| ### Unit Tests
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| ```python
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| def test_belief_updating():
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|     """Test belief updating mechanism."""
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|     agent = setup_test_agent()
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|     observation = generate_test_observation()
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|     
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|     initial_beliefs = agent.beliefs.copy()
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|     agent.update(observation)
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|     
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|     assert not np.allclose(agent.beliefs, initial_beliefs)
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|     assert is_normalized(agent.beliefs)
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| ```
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| 
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| ### Integration Tests
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| ```python
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| def test_agent_environment():
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|     """Test agent-environment interaction."""
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|     env = setup_test_environment()
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|     agent = setup_test_agent()
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|     
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|     observation = env.reset()
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|     for _ in range(100):
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|         action = agent.update(observation)
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|         observation, reward, done = env.step(action)
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|         if done:
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|             break
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| ```
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| 
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| ### Performance Tests
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| ```python
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| def test_performance():
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|     """Test system performance."""
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|     env = setup_benchmark_environment()
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|     agent = setup_benchmark_agent()
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|     
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|     start_time = time.time()
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|     run_benchmark(env, agent)
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|     end_time = time.time()
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|     
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|     assert end_time - start_time < MAX_TIME
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| ```
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| 
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| ## Related Resources
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| 
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| ### Documentation
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| - [[docs/guides/implementation_guides|Implementation Guides]]
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| - [[docs/api/implementation_api|Implementation API]]
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| - [[docs/research/implementation_research|Implementation Research]]
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| 
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| ### Knowledge Base
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| - [[knowledge_base/cognitive/implementation_concepts|Implementation Concepts]]
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| - [[knowledge_base/mathematics/implementation_math|Implementation Mathematics]]
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| - [[knowledge_base/agents/implementation_patterns|Implementation Patterns]]
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| 
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| ### Learning Resources
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| - [[learning_paths/implementation|Implementation Learning Path]]
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| - [[tutorials/implementation|Implementation Tutorials]]
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| - [[guides/implementation/best_practices|Implementation Best Practices]]  | 
