We consider the problem of exploration in meta reinforcement learning. T...
We propose a meta-learning approach for learning gradient-based reinforc...
Deep reinforcement learning (RL) methods generally engage in exploratory...
Count-based exploration algorithms are known to perform near-optimally w...
This paper describes InfoGAN, an information-theoretic extension to the
...
Scalable and effective exploration remains a key challenge in reinforcem...
Tackling pattern recognition problems in areas such as computer vision,
...