Introduction to Q-Learning

Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the environment (hence “model-free”), and it can handle problems with stochastic transitions and rewards without requiring adaptations.For any finite Markov decision process (FMDP), Q-learning finds an optimal policy in the sense of maximizing the expected value of the total reward over any and all successive steps, starting from the current state.

Resources

• What Is Q-Learning: The Best Guide To Understand Q-Learning
• Q-learning
• “Reinforcement Learning Specialization” By Coursera
• Q-Learning Explained - A Reinforcement Learning Technique