A python package to calculate Myerson values from game theory and use them as explanations for graph neural networks.
Project description
Calculate Myerson values and explain GNNs
This package implements the Myerson solution concept from cooperative game theory. The Myerson values attribute every player of a game their fair contribution to the games payoff. Myerson values are related to Shapley values but the player cooperation is restricted by a graph.
A graph neural network (GNN) can be treated as a coalition function for a game and the Myerson values can be used as feature attribution explanations to understand a model prediction. This package also implements Methods to explain PyG GNNs with Myerson values.
Calculating the Myerson value scales exponentially with bigger graphs / more players. Therfore, Monte Carlo sampling techniques were implemented to approximate the Myerson values.
Installation
Install the package with the following command:
pip install myerson
Examples and Documentation
Example uses can be found here. The full documentation can be found at https://myerson.readthedocs.io/.
Citation
TBD.
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