Curriculum Design for Accelerating Deep Reinforcement Learning in Contextual Multi-Task Settings with Target Distributions

The core message of this paper is to propose a novel curriculum strategy, PROCURL-TARGET, that effectively balances the need for selecting tasks that are neither too hard nor too easy for the agent while also progressing the agent's learning toward a target distribution over complex tasks by leveraging task correlations.