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In robotics, learning progress hypothesis refers to the proposal that agents are intrinsically motivated toward activities where their prediction errors are decreasing fastest, which organizes developmental stages. This meaning comes from Oudeyer (2007) in IEEE Transactions on Evolutionary Computation.[1]
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