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Explores a method where AI agents traverse their memory instead of performing traditional querying, potentially offering efficiency or reasoning benefits.
The author describes a problem where an LLM agent's memory graph gets corrupted by incorrect edges, and proposes using a declared ontology to validate writes and traversals. A test on 120 deliberately broken traversals caught all errors.