MemQ models memory evolution as a structured credit-assignment problem. A provenance DAG records which retrieved memories contributed to each newly created memory, while TD-style eligibility traces propagate feedback backward through those dependencies. This makes retrieval utility reflect both immediate usefulness and downstream influence, improving self-evolving memory agents across multi-step interaction, code, embodied reasoning, and expert QA tasks.
Credit assignment for agent memory, propagated through the provenance chains that make later memories possible.