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Understanding Bellman Equations in DRL by hesha.2021 is a document available to read on EtoBox.

What is Understanding Bellman Equations in DRL about?

The document discusses the application of Bellman Equations in Deep Reinforcement Learning (DRL) using a maze example where an agent aims to reach a trophy state while avoiding failure states. It explains how the agent learns to navigate the environment by exploring and backtracking to mark values of states leading to the goal. The Bellman Equation is introduced as a method to recursively calculate the optimal value function, which helps the agent determine the best actions to take based on expected rewards

Author

hesha.2021

Language

EN