Abstract
We design the first fully distributed algorithm for generalized Nash equilibrium seeking in aggregative games on a time-varying communication network, under partial-decision information, i.e., the agents have no direct access to the aggregate decision. The algorithm is derived by integrating dynamic tracking into a projected pseudo-gradient algorithm. The convergence analysis relies on the framework of monotone operator splitting and the Krasnosel'skii-Mann fixed-point iteration with errors.
Original language | English |
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Pages (from-to) | 2061-2075 |
Journal | IEEE Transactions on Automatic Control |
Volume | 66 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2021 |
Keywords
- Distributed algorithms
- multiagent systems
- network theory
- optimization method