Nicolò Botteghi

Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces

Reinforcement learning algorithms have proven to be capable of solving complicated robotics tasks in an end-to-end fashion without any need for hand-crafted features or policies. Especially in the context of robotics, in which the cost of real-world data is usually extremely high, Reinforcement Lear…