Hey guys, in this episode I explain what the Reinforcement Learning. In the episode I give some application of where Reinforcement Learning is being used and then I explain the basic concepts of an agent, an environment, a reward, the states and transitions. Then, I talk in a really high level about the ideia behind the main algorithms like Q-Learning, Deep-Learning, Actor Critic, PPO, DDPG... In the end I talk about the advanced Reinforcement Learning techniques that we have, like curriculum learning, hierarchical learning, imitation learning, meta learning and multi agent RL.

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