Reinforcement Learning, Deep Learning, Artificial Intelligence, Data Science.
the chance of bad decisions. Monitor the KL-divergence closely between the old and the new policy. Compare them with toy experiments using established methods. KL-divergence of 0.01 is reasonable and 10 is abnormal. For large KL-divergence or large spike, introduce a larger KL-divergence penalty.