Drift refers to the phenomenon where an agent's performance degrades gradually, often unnoticed until significant damage occurs.
Types
- Data drift: Input distribution changes from training
- Concept drift: Relationship between inputs and outputs changes
- Model drift: Agent behavior changes (through fine-tuning, updates)
Detection
Continuous monitoring of performance metrics with statistical tests for significant changes.