Knowledge Graph Integration

Aether Framework supports the integration of knowledge graphs to enable agents to store, query, and reason about structured information. This feature enhances the decision-making capabilities of agents by providing a persistent and queryable knowledge base.

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Key Features

1. Concept Storage Agents can store concepts, attributes, and relationships in a graph structure.

2. Reasoning and Querying Agents can query the knowledge graph to retrieve relevant information or relationships.

3. Visualization The knowledge graph can be visualized for better understanding and debugging.

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Example Workflow

1. Add Knowledge to the Graph

   from src.utils.knowledge_graph import KnowledgeGraph
   
   # Initialize the Knowledge Graph
   knowledge_graph = KnowledgeGraph()
   
   # Add a concept
   knowledge_graph.add_concept("AI Agent", {"role": "worker", "status": "active"})
   
   # Add a relationship between concepts
   knowledge_graph.add_relationship("AI Agent", "Swarm", "belongs_to")

2. Query the Knowledge Graph

   # Query a concept
   result = knowledge_graph.query_concept("AI Agent")
   print(f"Attributes of AI Agent: {result}")
   
   # Query relationships
   relationships = knowledge_graph.query_relationships("AI Agent")
   print(f"Relationships of AI Agent: {relationships}")

3. Visualize the Knowledge Graph

   # Visualize the graph
   knowledge_graph.visualize_graph(output_path="knowledge_graph.png")
   print("Knowledge graph saved as knowledge_graph.png")

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Benefits of Knowledge Graphs in Aether

1. Enhanced Reasoning Agents can use structured knowledge to make more informed decisions.

2. Collaboration Agents can share knowledge across the swarm, improving collective performance.

3. Persistent Memory Knowledge graphs serve as a long-term memory for agents.

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Best Practices

1. Use Attributes Effectively Add meaningful attributes to concepts for better querying and reasoning.

2. Structure Relationships Clearly Define relationships that reflect real-world connections (e.g., "belongs_to", "depends_on").

3. Regular Updates Periodically update the graph to reflect the latest knowledge and task history.

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