External representations and scientific understanding

Some of the robotics-related frameworks found in reinforcement learning settings provide explanations for policies that a robot selects at a given time step [132], [156].

“Moreover, some of the robotics-related frameworks found in reinforcement learning settings provide explanations for policies that a robot selects at a given time step [132], [156].”

Plan explicability is reformulated in terms of its comprehensibility by an end-user.

“As plan explicability is reformulated in terms of its comprehensibility by an end-user.”

The robot's model is adapted to the updates of human's model of the problem.

“The robot's model is adapted to the updates of human's model of the problem.”

Chakraborti et al. formulate the multi-model planning problem as a tuple consisting of the planner's model of the problem and the corresponding human approximation thereof.

“In addition, Chakraborti et al. formulate the multi-model planning problem as a tuple consisting of the planner's model of the problem and the corresponding human approximation thereof [132].”

Numerical counterfactual explanations can be extracted from interpretable feature-value pairs as a result of pruning in the search space.

“They can be extracted from interpretable featurevalue pairs as a result of pruning in the search space [132].”

It is worth noting that the run-time of explanation generation algorithms is reported in addition to the evaluation metrics for several frameworks.

“It is worth noting that the run-time of explanation generation algorithms is reported in addition to the evaluation metrics for several frameworks [132], [139], [146], [152], [156], [159].”