4.5 Value Iteration | DRL Course скачать в хорошем качестве

4.5 Value Iteration | DRL Course

In this lesson, we present "Value Iteration", a simplified and powerful Dynamic Programming (DP) method that merges policy evaluation and policy improvement into one streamlined process. You'll learn: • How value iteration updates value functions using the Bellman optimality equation • Why it converges faster than full policy iteration • How each iteration implicitly improves the policy while updating values • The stopping condition and its practical interpretation • The importance of value iteration as a bridge to modern RL algorithms 📺 This lesson is part of the "Deep Reinforcement Learning (DRL) Course". Watch the full course here:    • Deep Reinforcement Learning (DRL) Course   #ReinforcementLearning #DynamicProgramming #ValueIteration #BellmanOptimality #MachineLearning #AI #DeepLearning