In this regard, we propose a novel memory mechanism that represents past events in human language.

One of the phenomena of interest is that Q-learning (Watkins, 1989) is known to suffer from overestimation issues, since it takes a maximum operator overaset ofestimated action-values.

Here H is the horizon oftheRL environment, anddimR specifies thecomplexity ofthefunction class representing the reward function.

This component makes current Seldonian algorithms safe: the safety test checks whether necessary safety constraints are satisfiedwithhighprobability.