A repeated network game where agents have quadratic utilities that depend on information externalities -- an unknown underlying state -- as well as payoff externalities -- the actions of all other agents in the network -- is considered. Agents play Bayesian Nash Equilibrium strategies with respect to their beliefs on the state of the world and the actions of all other nodes in the network. These beliefs are refined over subsequent stages based on the observed actions of neighboring peers. This paper introduces the Quadratic Network Game (QNG) filter that agents can run locally to update their beliefs, select corresponding optimal actions, and eventually learn a sufficient statistic of the network's state. The QNG filter is demonstrated on a Cournot market competition game and a coordination game to implement navigation of an autonomous team.
A Douglas-Rachford Splitting Method for Solving Monotone Variational Inequalities in Linear-quadratic Dynamic Games
Rotterdam School of Management, Erasmus University（鹿特丹管理学院，伊拉斯姆斯大学）；Division of Decision and Control Systems, KTH Royal Institute of Technology（决策与控制系，皇家理工学院）；Delft Center for Systems and Control, Delft University of Technology（系统与控制中心，代尔夫特理工大学）
Intent Demonstration in General-Sum Dynamic Games via Iterative Linear-Quadratic Approximations
Oden Institute, University of Texas at Austin（德克萨斯大学奥斯汀分校奥登研究所）；Department of Economics, Stanford University（斯坦福大学经济学系）；Department of Electrical Engineering and Computer Sciences, University of California, Berkeley（加州大学伯克利分校电气工程和计算机科学系）；School of Computer Science, Carnegie Mellon University（卡内基梅隆大学计算机学院）
Linear-Quadratic Gaussian Games with Distributed Sparse Estimation
The University of Texas at Austin（德克萨斯大学奥斯汀分校）；Oden Institute for Computational Engineering and Sciences（奥登计算工程与科学学院）；DEVCOM Army Research Laboratory（美军研究开发司令部陆军研究实验室）
Linear quadratic graphon field games (LQ-GFGs) are defined to be LQ games which involve a large number of agents that are weakly coupled via a weighted undirected graph on which each node represents an agent. The links of the graph correspond to couplings between the agents' dynamics, as well as between the individual cost functions, which each agent attempts to minimize. We formulate limit LQ-GFG problems based on the assumption that these graphs lie in a sequence which converges to a limit graphon. First, under a finite-rank assumption on the limit graphon, the existence and uniqueness of so…
Characterization and Computation of Feedback Nash Equilibria in Scalar Discounted N-Player Linear Quadratic Games
IMT School for Advanced Studies Lucca（卢卡高等研究院）；Research Unit DYSCO (Dynamical Systems, Control, and Optimization) at IMT School for Advanced Studies Lucca（卢卡高等研究院动态系统、控制与优化研究单元）
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games
Department of Electrical and Computer Engineering & Coordinated Science Laboratory, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校电子工程与协调科学实验室部门）；Department of Operations Research and Financial Engineering, Princeton University（普林斯顿大学运筹学与金融工程系）
