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Tracking-Based Distributed Equilibrium Seeking for Aggregative Games
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DOI：10.1109/TAC.2024.3368967.png)
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摘要
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We propose fully distributed algorithms for Nash equilibrium seeking in aggregative games over networks. We first consider the case where local constraints are present and we design an algorithm combining, for each agent, the projected pseudogradient descent and a tracking mechanism to locally reconstruct the aggregative variable. To handle coupling constraints arising in generalized settings, we propose another distributed algorithm based on a recently emerged augmented primal-dual scheme and two tracking mechanisms to reconstruct, for each agent, both the aggregative variable and the coupling constraint satisfaction. Leveraging tools from singular perturbations analysis, we prove linear convergence to the Nash equilibrium for both schemes. Finally, we run extensive numerical simulations to confirm the effectiveness of our methods and compare them with state-of-the-art distributed equilibrium-seeking algorithms.
Keyword:
Couplings
Heuristic algorithms
Games
Convergence
Iterative methods
Distributed algorithms
Vectors
game theory
network analysis and control
optimization algorithms
期刊
IF:
7
论文数:
1.3W
被引数:
6.7W
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