Experience Replay

Experience Replay is a technique used in reinforcement learning where an AI learns from past experiences to improve future decision-making. Instead of learning solely from current interactions, the AI stores previous experiences (like successes and mistakes) in a memory buffer. During training, it randomly samples these past experiences to reinforce learning. This approach helps the AI overcome issues like forgetting and ensures it learns from a diverse set of scenarios, leading to better performance in complex tasks, much like how humans reflect on past experiences to make better choices in the future.