Concept准入规则
High-Probability Admission Rule
A verification mechanism in agent self-improvement frameworks that requires the use of fresh, independently validated data to judge whether a revision should be adopted, rather than relying on data seen during training. This reduces the risk of overfitting and hidden regressions, giving self-improvement statistical guarantees.
Timeline (last 90 days)
Oct 14
The high-probability admission rule requires using fresh, independently verified data to judge whether a revision should be adopted, rather than relying on data seen during training.
Unverified50%