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Let's suppose that our RL agent needs to play a game with different levels. If we train our RL agent sequentially or with sequential data, our agent will learn how to play level 1, but then it will learn to play level 2 differently, because our agent learns how to play level 2 and forgets how to play level 1, since now our model is fitted using only experiences from level 2.

How does an experience replay buffer change this? Can you explain this in simple terms?

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