Recent work has shown great promise in explaining neural network behavior. In particular,
feature attribution methods explain the features that are important to a model's prediction on …

1 Her work has been supported in part by an NRW grant for gender-sensitive universities
supporting her as a junior professor for Computational Social Choice and by the project …

The prevalent approach to problems of credit assignment in machine learning--such as
feature and data valuation--is to model the problem at hand as a cooperative game and …

In the usual models of cooperative game theory, the outcome of a coalition formation
process is either the grand coalition or a coalition structure that consists of disjoint coalitions …

Cooperative Game Theory: Basic Concepts and Computational Challenges Page 1 86 1541-1672/12/$31.00
© 2012 IEEE Ieee InTeLLIGenT SySTemS Published by the IEEE Computer Society AI AND …

When autonomous agents interact in the same environment, they must often cooperate to
achieve their goals. One way for agents to cooperate effectively is to form a team, make a …

Module checking is a decision problem to formalize the verification of (possibly multi-agent)
systems that must adapt their behavior to the input they receive from the environment, also …

The computational complexity of the partition, 0-1 subset sum, unbounded subset sum, 0-1
knapsack and unbounded knapsack problems and their multiple variants were studied in …

In many real-world settings, the structure of the environment constrains the formation of
coalitions among agents. These settings can be represented by characteristic function …

Coalitional games allow subsets (coalitions) of players to cooperate to receive a collective
payoff. This payoff is then distributed “fairly” among the members of that coalition according …