juniorQ-Learning
What is convergence in Q-Learning?
Updated May 17, 2026
Short answer
Convergence means Q-values stabilize over time.
Deep explanation
When updates no longer significantly change Q-values, the optimal policy is learned.
Real-world example
Stable navigation policy in robotics.
Common mistakes
- Stopping training too early.
Follow-up questions
- Does Q-Learning always converge?