TY - JOUR
T1 - Learning generalized Nash equilibria in multi-agent dynamical systems via extremum seeking control
AU - Krilašević, Suad
AU - Grammatico, Sergio
PY - 2021
Y1 - 2021
N2 - In this paper, we consider the problem of learning a generalized Nash equilibrium (GNE) in strongly monotone games. First, we propose semi-decentralized and distributed continuous-time solution algorithms that use regular projections and first-order information to compute a GNE with and without a central coordinator. As the second main contribution, we design a data-driven variant of the former semi-decentralized algorithm where each agent estimates their individual pseudogradient via zeroth-order information, namely, measurements of their individual cost function values, as typical of extremum seeking control. Third, we generalize our setup and results for multi-agent systems with nonlinear dynamics. Finally, we apply our methods to connectivity control in robotic sensor networks and almost-decentralized wind farm optimization.
AB - In this paper, we consider the problem of learning a generalized Nash equilibrium (GNE) in strongly monotone games. First, we propose semi-decentralized and distributed continuous-time solution algorithms that use regular projections and first-order information to compute a GNE with and without a central coordinator. As the second main contribution, we design a data-driven variant of the former semi-decentralized algorithm where each agent estimates their individual pseudogradient via zeroth-order information, namely, measurements of their individual cost function values, as typical of extremum seeking control. Third, we generalize our setup and results for multi-agent systems with nonlinear dynamics. Finally, we apply our methods to connectivity control in robotic sensor networks and almost-decentralized wind farm optimization.
KW - Extremum seeking control
KW - Generalized Nash equilibrium learning
KW - Multi-agent systems
UR - http://www.scopus.com/inward/record.url?scp=85112594121&partnerID=8YFLogxK
U2 - 10.1016/j.automatica.2021.109846
DO - 10.1016/j.automatica.2021.109846
M3 - Article
AN - SCOPUS:85112594121
SN - 0005-1098
VL - 133
JO - Automatica
JF - Automatica
M1 - 109846
ER -