This is the third instance in our Reinforcement Learning Reading Group series.
The paper for this week is Constrained Policy Optimization (https://arxiv.org/abs/1705.10528). It will be presented by Joshua Achiam.
This reading group is covering recent advances in Reinforcement Learning. You are expected to understand the basics of Reinforcement Learning, such as states, actions and policies, we will not explain them at the meetup. Here's a decent introduction to RL: http://neuro.cs.ut.ee/demystifying-deep-reinforcement-learning/
Reading the paper in advance is highly encouraged.