A Measure of Explanatory Effectiveness
Dylan Cope Peter McBurney
In most conversations about explanation and AI, the recipient of the
explanation (the explainee) is suspiciously absent, despite the problem being
ultimately communicative in nature. We pose the problem `explaining AI systems'
in terms of a two-player cooperative game in which each agent seeks to maximise
our proposed measure of explanatory effectiveness. This measure serves as a
foundation for the automated assessment of explanations, in terms of the
effects that any given action in the game has on the internal state of the
explainee.