HEX: Human-in-the-loop Explainability via Deep Reinforcement Learning. (arXiv:2206.01343v1 [cs.LG])

The use of machine learning (ML) models in decision-making contexts,
particularly those used in high-stakes decision-making, are fraught with issue
and peril since a person - not a machine - must ultimately be held accountable
for the consequences of the decisions made using such systems. Machine learning
explainability (MLX) promises to provide decision-makers with
prediction-specific rationale, assuring them that the model-elicited
predictions are made for the right reasons and are thus reliable. Few works
explicitly consider this key human-in-the-loop (HITL) …

arxiv explainability hex human learning loop reinforcement reinforcement learning