Episode Buffer

An Episode Buffer is a temporary storage area used in reinforcement learning algorithms to hold recent experiences or data points, called "episodes." It allows the system to efficiently sample past experiences during training, which helps improve learning stability and performance. By mixing recent and older experiences, the model can better generalize and avoid overfitting to specific situations. Think of it as a replay folder that stores recent activity, enabling the system to learn more effectively from a variety of past scenarios without having to revisit everything in real-time.