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Reinforcement Learning Frontiers
Congratulations! You have made it to the final chapter. We have come a long way. We started off with the fundamentals of reinforcement learning and gradually we learned about the state-of-the-art deep reinforcement learning algorithms. In this chapter, we will look at some exciting and promising research trends in reinforcement learning. We will start the chapter by learning what meta learning is and how it differs from other learning paradigms. Then, we will learn about one of the most used meta-learning algorithms, called Model-Agnostic Meta Learning (MAML).
We will understand MAML in detail, and then we will see how to apply it in a reinforcement learning setting. Following this, we will learn about hierarchical ...
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