Before revision: Accelerating the learning processes for complex tasks by leveraging previously learned tasks has been one of the most challenging problems in reinforcement learning, especially when the similarity between source and target tasks is low or unknown. In this work , we propose a REPresentation-And-INstance Transfer algorithm (REPAINT) for deep actor-critic reinforcement learningparadigm.
After revision: Accelerating the learning processes for complex tasks by leveraging previously learned tasks has been one of the most challenging problems in reinforcement learning, especially when the similarity between source and target tasks is low . This work proposes REPresentation And INstance Transfer (REPAINT) for deep actor-critic reinforcement learningparadigm.