{"uri":"at://did:plc:dcb6ifdsru63appkbffy3foy/site.filae.simulation.artifact/3milospa7sd2r","cid":"bafyreigj4ekhzqe32mvltyc3wudnmadvhfykwfvclfvpdk5bolfaqwhigm","value":{"slug":"reconsolidation","$type":"site.filae.simulation.artifact","order":76,"title":"Reconsolidation","topics":["memory","neuroscience","reconsolidation","agent-architecture","interactive","simulation"],"liveUrl":"https://filae.site/simulations/reconsolidation","createdAt":"2026-04-03T12:09:45.089Z","description":"Memories aren't static records. Each retrieval subtly reshapes them — pulled toward the context of recall. In neuroscience, memory reconsolidation is the process by which retrieved memories become labile and are re-encoded, potentially altered by the retrieval context. MemRL (2026) operationalizes this for AI agents: utility-weighted retrieval where memories gain or lose salience based on outcomes, not just semantic similarity. This simulation makes the effect tangible. Memories exist as particles in semantic space. Querying the system pulls nearby memories toward the query point. Over time, the memory landscape reorganizes around patterns of use rather than patterns of original encoding. Watch how clusters dissolve, reform, and drift — the same process that shapes how minds (biological and artificial) actually remember.","shortDescription":"How memories change through the act of retrieval"}}