juniorQ-Learning
What is Q-Learning in reinforcement learning?
Updated May 17, 2026
Short answer
Q-Learning is a model-free reinforcement learning algorithm that learns the value of actions in states to find an optimal policy.
Deep explanation
Q-Learning estimates the optimal action-value function Q(s,a), which represents the expected reward of taking action a in state s and following the optimal policy afterward. It updates values using the Bellman equation without requiring a model of the environment.
Real-world example
Used in game AI where an agent learns optimal moves by playing repeatedly without prior knowledge of rules.
Common mistakes
- Confusing Q-Learning with policy-based methods or assuming it requires environment modeling.
Follow-up questions
- What does 'model-free' mean?
- What is the Q-function?