Semantic Memory
Master how AI agents store and organize facts, knowledge, and concepts in structured semantic memory systems
Your Progress
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Congratulations! You've mastered Semantic Memory—the foundation of knowledge storage and reasoning in AI agents. You now understand how agents organize facts, build knowledge graphs, and reason over complex information.
Review the key takeaways below and check them off as you confirm your understanding. This structured knowledge will serve you as you explore more advanced agent capabilities.
✅ Key Takeaways Checklist
Semantic memory stores general facts and knowledge, unlike episodic memory which stores personal experiences
Key components include concepts (entities), relationships (connections), attributes (properties), and hierarchies (categories)
Flat lists are simple but lack relationships; taxonomies provide hierarchies; ontologies offer rich semantic networks
Ontologies support multiple relationship types, advanced reasoning, and capture domain complexity
Schemas and frames provide templates for organizing related concepts with predefined slots
Triples (Subject-Predicate-Object) are the fundamental units of knowledge graphs
Knowledge graphs are webs of interconnected concepts with labeled, typed relationships
Agents can traverse graphs to discover implicit knowledge and make inferences
Real-world uses include Google Search, recommendation systems (Netflix/Spotify), and AI assistants
Retrieval strategies include exact match, keyword search, semantic search, and graph traversal
Reasoning methods include deduction (applying rules), induction (generalizing), and abduction (best explanation)
Query languages like SPARQL enable pattern matching and complex queries over knowledge graphs
Semantic memory enables agents to answer questions, make inferences, and provide consistent information
Balance reasoning depth with performance—complex inference is powerful but slower
Use ontologies for semantic memory in production agents to support sophisticated reasoning and domain expertise
🚀 What's Next?
Build on This Foundation: Semantic memory is one of three core memory types. You've already explored episodic and procedural memory—now you understand the complete picture.
Practical Applications: Try implementing a simple knowledge graph for a domain you're familiar with (recipes, movies, or software libraries). Use triples and see how querying works.
Advanced Topics: Explore vector embeddings for semantic search, graph databases like Neo4j, or reasoning engines like OWL/Protégé.
Next Module: Episodic Memory
Expand your knowledge of agentic AI systems