As others have pointed out , the Shapley value is not the only concept from cooperative game theory that could be used to explain machine learning predictions. A recent example is GStarX, which uses a novel, structure-aware solution concept to explain graph neural networks . An older solution concept, less popular than the Shapley value (although acknowledged in ), is that of Myerson values . Like Shapley values, Myerson values attribute a value to each player of a game, denoting their contribution to the final outcome of the game. Myerson's idea was to restrict the players' possible cooperation depending on a series of bilateral agreements between players, i.e., a graph in which the players form the nodes and the edges show possible cooperation, resulting in a structure-aware solution concept. In these games, any value gained by cooperation is only accessible in coalitions, in which a link between the cooperating players exists.