A context-based meta-reinforcement learning approach to efficient hyperparameter optimization

•A context helps the agent to learn knowledge from previous tasks.•A simple multi-task objective meta-training procedure is proposed to run faster.•A quadratic penalty technique is used to preserve the historical experience.•A predictive model is applied to further accelerate the adaptation phase.