Reinforcement Learning and Deep RL Python Theory and Projects - Target Network and Recap

The video tutorial explains the importance of selecting random batches from replay memory to avoid correlation issues in training neural networks. It introduces the concept of a target network, which is a replica of the policy network, and its role in stabilizing the learning process. The tutorial details the calculation of the loss function using Q values from both the policy and target networks, emphasizing the Bellman equation. It concludes with an overview of the algorithm and outlines the next steps for implementation in Python.

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