This work proposes a dual-agents reasoning strategy under the Variational EM framework to achieve efficient exploration in the meta-RL problem.

Despite recent success of deep neural networks, it remains challenging to efficiently learn new visual concepts from limited training data. To address this problem, a prevailing strategy is to build a meta-learner that learns prior knowledge on …