Reinforcement Learning, Machine Learning, Deep Learning, Artificial Intelligence.
current policy itself. 2. Exploration: On-policy methods tend to have a built-in exploration mechanism, as they continue to explore the environment to gather new experiences. 3. Sample Efficiency: On-policy methods might require more data to converge, as they are constrained by the data collected