Before revision:  HER is known as a sample-efficient replay method that enhances the performance of off-policy DRL algorithms by allowing them to learn from both failures and successes.
After revision:  HER is known as a sample-efficient replay method that enhances the performance of off-policy DRL algorithms by allowing the agent to learn from both failures and successes.