Explain a scenario where an AI Agent failed to adapt dynamically. How would you troubleshoot this?

Answer:

Scenario: An e-commerce inventory AI Agent overstocked seasonal items due to outdated trend analysis.
Troubleshooting Steps:

1. Root Cause Analysis: Check for data drift or stale training data 7.
2. Model Retraining: Use real-time sales data and ensemble methods (Random Forest) to improve predictions 8.
3. Feedback Loops: Integrate A/B testing to validate adjustments 9.

Result: Reduced overstocking by 30% through adaptive learning, as demonstrated in retail automation