Accuracy-based Curriculum Learning in Deep Reinforcement Learning

25 Jun 2018Pierre FournierOlivier SigaudMohamed ChetouaniPierre-Yves Oudeyer

In this paper, we investigate a new form of automated curriculum learning based on adaptive selection of accuracy requirements, called accuracy-based curriculum learning. Using a reinforcement learning agent based on the Deep Deterministic Policy Gradient algorithm and addressing the Reacher environment, we first show that an agent trained with various accuracy requirements sampled randomly learns more efficiently than when asked to be very accurate at all times... (read more)

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