Name
Abstract | ||
|---|---|---|
We consider network aggregative games where each player minimizes a cost function that depends on its own strategy and on a convex combination of the strategies of its neighbors. As a first contribution, we propose a class of distributed algorithms that can be used to steer the strategies of the rational agents to a Nash equilibrium configuration, with guaranteed convergence under different sufficient conditions depending on the cost functions and on the network. A distinctive feature of the proposed class of algorithms is that agents use optimal responses instead of gradient type of strategy updates. As a second contribution, we show that the algorithm suggested for network aggregative games can also be used to recover a Nash equilibrium of average aggregative games (i.e., games where each agent is affected by the average of the strategies of the whole population) in a distributed fashion, that is, without requiring a central coordinator. We apply our theoretical results to multi-dimensional, convex-constrained opinion dynamics and to demand-response schemes for energy management. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.automatica.2020.108959 | Automatica |
Keywords | DocType | Volume |
Deterministic aggregative games,Best response dynamics,Distributed algorithms,Multi-agent systems | Journal | 117 |
Issue | ISSN | Citations |
1 | 0005-1098 | 2 |
PageRank | References | Authors |
0.38 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francesca Parise | 1 | 54 | 8.79 |
| Sergio Grammatico | 2 | 173 | 25.63 |
| Basilio Gentile | 3 | 25 | 4.12 |
| John Lygeros | 4 | 2742 | 319.22 |