Deep Imitation Learning
Deep Imitation Learning



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„Deep Imitation Learning“

Deep Imitation Learning (DIL) is a type of reinforcement learning (RL) technique that uses a pre-trained model to learn a task by imitating expert actions. It is based on the idea that a model can learn a task better by imitating a human expert than by learning it from scratch. In DIL, the expert performs the task in an environment and the model records the expert’s behavior. The model then utilizes this data to learn the task by imitating the expert. This allows the model to quickly learn the task from the expert's experience, without the need for expensive trial-and-error exploration.