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Techniques are disclosed that enable training a meta-learn ing model, for use in causing a robot to perform a task, using imitation learning as well as reinforcement learning. Some implementations relate to training the meta-learning model using imitation learning based on one or more human guided demonstrations of the task. Additional or alternative imple mentations relate to training the meta-learning model using reinforcement learning based on trials of the robot attempt ing to perform the task. Further implementations relate to using the trained meta-learning model to few shot (or one shot) learn a new task based on a human guided demonstra tion of the new task.