… review for the economic and game theoretic approaches proposed in the … theories commonly
used in incentive mechanism design. Then, we review applications of game theory and …

… Game theory in federated learning The closest work to … game theory to analyze federated
learning games is Hasan [2021], which gives conditions for Nash stability in federated learning. …

… Federated learning (FL) has emerged as a promising technique to train a global attack
detection model on several edge devices, without sharing their private sensitive data [7] [8]. …

… Although all of these works used the game theory, none of them focused on the averaging
… in federated learning. In this paper, we use the game theory to propose a robust federated …

… best datasets to federated learning, we need to … a game-theoretic model for analyzing the
FL incentive mechanism design problem. We provide a checklist to specify heterogenous game …

… To accelerate the training speed to achieve higher accuracy in real time, in this work we
apply federated learning across multiple UAVs through UAV-to-UAV communications. The …

… federated learning architecture to a learning market with privacy preserving. In the learning
market, data owners apply federated learning … from data, a learning service provider collects …

… Differential Privacy and Game Theory Game theory involves strategic decision-making by
rational players. As a rigorous model, differential privacy provides many desirable properties …

… in model training for federated learning and obtain … game theory to the study of incentives
in federated learning, and plays a leading role in the study of incentives in federated learning. …

… To address the above two key issues, we will leverage the game theoretic modeling approach
for developing a comprehensive analytical framework for participantcentric FL. We take …