Oct 2026· C2 Science and Technology· 0 citations· 25 references
TL;DR
A distributed online gradient-descent algorithm is developed to seek the time-varying Nash equilibrium in the game and is proven to achieve a sublinear dynamic regret bound via an appropriate learning rate, provided that the path variations grow sublinearly.
Abstract
This paper investigates noncooperative online games in multi-agent systems with time-delay feedback constraints. In these games, all players individually minimize their own time-varying costs, yet these costs are coupled through the joint strategies of the entire group. The gradient feedback available to the player is subject to unknown, heterogeneous delays that vary across players and time instants. To address these challenges, a distributed online gradient-descent algorithm is developed to seek the time-varying Nash equilibrium in the game. The algorithm is proven to achieve a sublinear dynamic regret bound via an appropriate learning rate, provided that the path variations grow sublinearly. Finally, an online electricity market game with time-varying delays is provided to illustrate the effectiveness of the algorithm.
We consider cooperative and iterative tasks involving multiple agents whose interactions are modeled as a dynamic game with shared constraints. We propose a general learning framework applicable to nonlinear and nonconvex dynamic games that uses previously executed feasible trajectories to construct a sampled joint saf...
This paper addresses the Nash equilibrium seeking problem for multi-coalition games with heterogeneous agent dynamics under limited communication resources. To reduce network overhead and meet real-time decision-making demands, a distributed algorithm integrating event-triggered communication with predefined-time contr...
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This paper is concerned with a distributed model predictive control (DMPC) problem for multi-agent systems (MASs) with noncooperative games under undirected switching topologies. With respect to parameter uncertainties of MASs and complicated information communication between neighbors under changing topologies, a dual...
Ling-Ling Zhang, Yan Song, Yuan Yuan· IEEE Transactions on Automat...· 0 citations
This work proposes a fast and versatile interior point solver for constrained dynamic games, along with a computationally efficient second-order correction that increases the probability of converging to a local GNE solution in constrained dynamic games.
Networked decentralized optimal equilibrium learning dynamics in which agents generate randomized semantic content/discontent signals from local payoff comparisons and exchange time-stamped time-stacked tables rather than raw actions, payoff information or local estimates/parameters are proposed.
Seref Taha Kiremitci, Muhammed O. Sayin· 0 citations
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