NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:7793
Title:Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck

According to the reviews, this submission is quite easy to evaluate. All reviewers view the paper as presenting a novel and promising technique for regularization via noise injection along with variational information bottleneck. Performance benefits are also shown by state-of-art performance in the CoinRunner domain. Reviewers also found the author feedback quite convincing, as two of the three reviewers raised their overall scores. There were only a few issues mentioned in the revised reviews, and these issues were considered as minor. With final scores of (8, 7, 6) this appears to be an easy accept for NeurIPS.