Q-Learning
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What is Q-Learning?
Q-Learning is a type of reinforcement learning algorithm that aims to find the best action to take given the current state. It works by learning a "Q-function," which estimates the expected cumulative reward for taking a specific action in a particular state and following the optimal policy thereafter. This Q-function is iteratively updated based on the agent's experiences, allowing it to learn the optimal policy without needing a model of the environment.
Free resources to learn Q-Learning
More in stage 26: Metrics to Evaluate
Q-Learning: common questions
Can I learn Q-Learning in Hindi?
This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Q-Learning in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.
Is this Q-Learning tutorial for beginners?
It is lesson 108 of 150 in the free Machine Learning roadmap, in stage 26, Metrics to Evaluate. If you are new to Machine Learning, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.