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In this video, I explain one of the most important concepts in Reinforcement Learning (RL) — the Value Function, written as V(s). You’ll learn: ✅ What V(s) means in RL ✅ Why it matters for decision-making ✅ How agents learn the value of different states ✅ How to calculate V(s) using the Bellman Expectation Equation ✅ A simple, intuitive example using the classic Snake game 🐍 This tutorial is designed for beginners in Machine Learning, Artificial Intelligence, and Reinforcement Learning who want to build a strong foundation. By the end, you’ll have a clear understanding of how V(s) works and how to apply it in AI agent training. 📩 For collaborations, sponsorships, or inquiries: [email protected] 🔔 Don’t forget to like, comment, and subscribe if you find this helpful!
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