Generating Explanations from Deep Reinforcement Learning Using Episodic Memory. (arXiv:2205.08926v1 [cs.AI])

Deep Reinforcement Learning (RL) involves the use of Deep Neural Networks
(DNNs) to make sequential decisions in order to maximize reward. For many tasks
the resulting sequence of actions produced by a Deep RL policy can be long and
difficult to understand for humans. A crucial component of human explanations
is selectivity, whereby only key decisions and causes are recounted. Imbuing
Deep RL agents with such an ability would make their resulting policies easier
to understand from a human perspective …

ai arxiv learning memory reinforcement reinforcement learning