Machine Learning, AI, Reinforcement Learning, Optimization, Neural Networks.
selecting such a set of parameters. On average, it would take 1561 random experiments before matching the accuracy of policy gradients! In this case, PG is roughly 6.25x more efficient than random search. That’s lower efficiency than we saw for discrete parameters (>10x), but still pretty