Imitation learning is a type of machine learning where an agent learns to perform a task by imitating the behavior of an expert. Instead of relying on a reward function, as in reinforcement learning, the agent learns directly from demonstrations or data provided by the expert. Common uses include robotics (teaching robots new skills), autonomous driving (learning driving policies from human drivers), and game playing (creating AI agents that play like human experts).
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