Reinforcement Learning, Deep Learning, Machine Learning, Neural Networks, Algorithms.
learning is often to learn an optimal policy that maximizes the expected cumulative reward over time. This is typically achieved through trial and error, where the agent interacts with the environment, observes the resulting rewards and transitions to new states, and updates its policy based on the