dc.creator | Carnevale, Guido | es |
dc.creator | Fabiani, Filippo | es |
dc.creator | Fele, Filiberto | es |
dc.creator | Margellos, Kostas | es |
dc.creator | Notarstefano, Giuseppe | es |
dc.date.accessioned | 2024-06-28T11:50:36Z | |
dc.date.available | 2024-06-28T11:50:36Z | |
dc.date.issued | 2024-02 | |
dc.identifier.citation | Carnevale, G., Fabiani, F., Fele, F., Margellos, K. y Notarstefano, G. (2024). Tracking-Based Distributed Equilibrium Seeking for Aggregative Games. IEEE Transactions on Automatic Control. https://doi.org/10.1109/TAC.2024.3368967. | |
dc.identifier.issn | 0018-9286 | es |
dc.identifier.issn | 1558-2523 | es |
dc.identifier.issn | 2334-3303 | es |
dc.identifier.uri | https://hdl.handle.net/11441/160970 | |
dc.description | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. | es |
dc.description.abstract | 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, (i) the projected pseudo-gradient descent and (ii) a tracking mechanism to locally reconstruct the aggregative variable. To handle coupling constraints arising in generalized settings, we propose another distributed algorithm based on (i) a recently emerged augmented primal-dual scheme and (ii) 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. | es |
dc.format | application/pdf | es |
dc.format.extent | 16 p. | es |
dc.language.iso | eng | es |
dc.publisher | IEEE | es |
dc.relation.ispartof | IEEE Transactions on Automatic Control. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Couplings | es |
dc.subject | Heuristic algorithms | es |
dc.subject | Games | es |
dc.subject | Convergence | es |
dc.subject | Iterative methods | es |
dc.subject | Distributed algorithms | es |
dc.subject | Vectors | es |
dc.subject | Game theory | es |
dc.subject | Optimization algorithms | es |
dc.subject | Network analysis and control | es |
dc.subject | Distributed algorithms | es |
dc.title | Tracking-Based Distributed Equilibrium Seeking for Aggregative Games | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.projectID | BR22GR01 | es |
dc.relation.projectID | RYC2021-033960-I | es |
dc.relation.projectID | PID2022-142946NA-I00 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/10443511 | es |
dc.identifier.doi | 10.1109/TAC.2024.3368967 | es |
dc.journaltitle | IEEE Transactions on Automatic Control | es |
dc.contributor.funder | Ministerio de Asuntos Exteriores y Cooperación Internacional. Italia | es |
dc.contributor.funder | Ministerio de Ciencia, Innovación y Universidades. España | es |
dc.contributor.funder | Agencia Estatal de Investigación. España | es |
dc.contributor.funder | European Union (UE) | es |
dc.contributor.funder | European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER) | es |