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Semantic Memory Networks(SMN)
General world knowledge systems divorced from specific acquisition context, supporting factual knowledge and concept relationships for multi-agent agentic AI systems
In 30 seconds
- What
- Stores factual knowledge and concept relationships in a shared graph structure, enabling agents to query and link information across domains without needing original context.
- When to use
- Multiple agents need consistent access to world facts, concept hierarchies, or domain relationships that persist across conversations and queries.
- Watch out
- Knowledge graphs become stale or inconsistent when updates from different agents conflict, and semantic similarity matching can return plausible but incorrect connections.
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Semantic Memory Networks: Overview
General world knowledge systems divorced from specific acquisition context, supporting factual knowledge and concept relationships for multi-agent agentic AI systems
- Factual knowledge representation
- Concept relationship mapping
- Context-independent knowledge
- Semantic similarity matching
- Knowledge graph structures
- Multi-agent knowledge sharing
- Hierarchical concept organization
- Cross-domain knowledge linking
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References
The papers, specifications, and repositories this pattern is based on.
- Can Knowledge Graphs Reduce Hallucinations in LLMs? A Survey (Pan et al., 2024)arXiv:2311.07914
- Semantic Networks: Computational Aspects (Sowa, 2014)
- Knowledge Representation and Reasoning (Brachman & Levesque, 2004)
- The Semantic Web and Knowledge Graphs (Hogan et al., 2021)arXiv:2003.02320
- Ontologies and Knowledge Graphs: Theory and Practice (Staab & Studer, 2009)
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