Experience Replay Memory

Experience Replay Memory is a technique used in reinforcement learning where a system stores past experiences—such as actions taken and their outcomes—in a memory bank. During training, it randomly samples from this collection to learn from a diverse set of previous situations. This approach improves learning efficiency and stability by breaking the correlation between consecutive experiences, allowing the system to better understand which actions lead to successful results over time. Essentially, it enables the model to review and learn from its past in a more effective way.