NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:7143
Title:A Composable Specification Language for Reinforcement Learning Tasks

The paper presents and evaluates SPECTRL, a framework for transforming formal specifications of tasks into shaped reward function. The reviewers agreed that, while it is not obvious that this paper will be extremely impactful, it is nonetheless interesting, convincing, and clearly written. After some discussion, the consensus leans towards acceptance, although with some outstanding issues (especially regarding the cartpole results) which should be addressed before publication. It is also highly recommended that a reference implementation of this method be released for use within the community, although it is not in my power to make this a formal requirement for publication.