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cs.GT2025
Scalable Neural Incentive Design with Parameterized Mean-Field Approximation
Nathan Corecco, Batuhan Yardim, Vinzenz Thoma +2
Designing incentives for a multi-agent system to induce a desirable Nash equilibrium is both a crucial and challenging problem appearing in many decision-making domains, especially…
math.OC2025
A Variational Inequality Approach to Independent Learning in Static Mean-Field Games
Batuhan Yardim, Semih Cayci, Niao He
Competitive games involving thousands or even millions of players are prevalent in real-world contexts, such as transportation, communications, and computer networks. However, lear…