Automated curriculum generation through setter-solver interactions

ICLR 2020 Anonymous

Reinforcement learning algorithms use correlations between policies and rewards to improve agent performance. But in dynamic or sparsely rewarding environments these correlations are often too small, or rewarding events are too infrequent to make learning feasible... (read more)

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