Imitation Learning and Inverse RL

Learning from demonstration is often called imitation learning. In the imitation learning setting, we have expert demonstrations and train our agent to mimic those expert demonstrations. Learning from demonstrations has many benefits, including helping an agent to learn more quickly. There are several approaches to perform imitation learning, and two of them are supervised imitation learning and Inverse Reinforcement Learning (IRL).

First, we will understand how we can perform imitation learning using supervised learning, and then we will learn about an algorithm called Dataset Aggregation (DAgger). Next, we will learn how to use demonstration data in a DQN using an algorithm called Deep Q Learning from ...

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