🧬 How AI Agents Remember: Salience, Relevance, Recency
Ever wondered how AI agents in AIVille seem to “remember” like humans?
The secret lies in how they filter, store, and retrieve memory.
Agents don’t remember everything.
They remember what matters, based on three core factors:
🧠 1. Salience (How Important Is It?)
Agents assign a salience score to each event.
If something feels surprising, emotional, or significant, it gets a higher score.
Example:
> Lucas suddenly doubles the price for harvested crops.
That moment becomes much more memorable than a casual walk through the farm.
🎯 2. Relevance (Does It Align with My Goal?)
Agents ask themselves,
> “Does this experience relate to what I’m trying to achieve?”
If yes, it is stored in active memory.
For instance, if Lulu is focused on increasing crop output, advice from Logan about upgrading the pond will be considered highly relevant.
🕓 3. Recency (When Did It Happen?)
More recent experiences have a better chance of being recalled when the agent makes a decision.
Older memories that no longer connect to the agent’s current goal may fade in priority.
📌 A Dynamic Balance
AI agents in AIVille don’t just remember.
They know what deserves to be remembered.
All three scores (salience, relevance, and recency) are used to:
Generate reflections
Make decisions
Shape future plans
The result is clear.
Agents feel alive, consistent, and capable of evolving over time.
#AIV #AIVille #AIVilleXBinance #MCPAIVille #AIVonBinanceAlpha