Abstract: Examples described herein provide a method for explaining neuro-symbolic reinforcement learning reasoning in a neuro-symbolic neural network for neuro-symbolic artificial intelligence. The method includes selecting an action from among possible candidates taken in an environment, wherein the action comprises a pair of a verb and an entity and displaying one or more logical facts that are extracted from natural observation sentences of the environment. The method also includes visualizing contrastive information for a current state and a goal state which is from external knowledge and displaying trained rules in the neuro-symbolic neural network for neuro-symbolic artificial intelligence, wherein, in response to a first user selection of the action, highlighting each pair of the verb and the entity and a fired predicate corresponding to the first user selection.