Title:
Approximating the Shapley value in transportation network cooperative games
 

Co-authors:
Yuval Hadas (Bar-Ilan University, Israel), Mauro Passacantando (University of Milan-Bicocca, Italy), Marcello Sanguineti (University of Genova, Italy)

 

Abstract: 
The Shapley value is a well-established concept in cooperative game theory, which serves as a metric for quantifying the importance of each player in a transferable utility game. Recently, it has found application in assessing the relevance of individual nodes or arcs within a network. However, in this framework, the exact evaluation of the Shapley value is often computationally expensive, particularly in the case of extensive networks. This study deals with the problem of approximating the Shapley value in a transferable utility game defined over a network, wherein the characteristics of the network are parameterized by a variable of interest (for instance, the traffic demand). We analyze the smoothness of the Shapley value with respect to this parameter and leverage such smoothness to theoretically justify the use of machine-learning techniques for its approximate computation. Additionally, we present potential extensions of this research.

 

Link Google Meet: 
https://meet.google.com/skr-mtnd-ied