Reinforcement Learning, Machine Learning, Deep Learning, Artificial Intelligence.
current policy might exploit previously learned data. 3. Sample Efficiency: Off-policy methods can be more sample-efficient since they can learn from a broader range of experiences collected over multiple policy iterations. Example of Off-Policy RL: Consider a self-driving car that is learning to