PREPING: Zero-Task Agent Memory Construction via Self-Practice
The PREPING framework builds agent memory before any real tasks by using controlled synthetic practice to create reusable procedural memory. It introduces a proposer-guided system where a Proposer generates tasks based on a control state, and a Validator filters out infeasible experiences. This method significantly improves performance over no-memory baselines and offers deployment cost savings.