Open-Loop Nash Equilibria in a Class of Linear-Quadratic Difference Games With Constraints

2015 ◽  
Vol 60 (9) ◽  
pp. 2559-2564 ◽  
Author(s):  
Puduru Viswanadha Reddy ◽  
Georges Zaccour
Keyword(s):  
Nash Equilibria ◽  
Open Loop ◽  
Linear Quadratic

Slow and Steady Wins the Race: Approximating Nash Equilibria in Nonlinear Quadratic Tracking Games Steter Tropfen höhlt den Stein: Approximation von Nash Gleichgewichten in Nicht-linearen Dynamischen Spielen

2018 ◽  
Vol 238 (6) ◽  
pp. 541-569
Author(s):  
Ivan Savin ◽  
Dmitri Blueschke ◽  
Viktoria Blueschke-Nikolaeva
Keyword(s):  
Objective Function ◽  
Nash Equilibria ◽  
Control Variable ◽  
Dynamic Game ◽  
Inequality Constraint ◽  
Open Loop ◽  
Linear Quadratic ◽  
Traditional Methods ◽  
Dynamic Tracking ◽  
Quadratic Tracking

Abstract We propose a new method for solving nonlinear dynamic tracking games using a meta-heuristic approach. In contrast to ‘traditional’ methods based on linear-quadratic (LQ) techniques, this derivative-free method is very flexible with regard to the objective function specification. The proposed method is applied to a three-player dynamic game and tested versus a derivative-dependent method in approximating solutions of different game specifications. In particular, we consider a dynamic game between fiscal (played by national governments) and monetary policy (played by a central bank) in a monetary union. Apart from replicating results of the LQ-based techniques in a standard setting, we solve two ‘non-standard’ extensions of this game (dealing with an inequality constraint in a control variable and introducing asymmetry in penalties of the objective function), identifying both a cooperative Pareto and a non-cooperative open-loop Nash equilibria, where the traditional methods are not applicable. We, thus, demonstrate that the proposed method allows one to study more realistic problems and gain better insights for economic policy.

Titik Setimbang Nash pada Permainan Linear Kuadratik Non-kooperatif dengan Asumsi Keseluruhan Pemain dapat Menstabilkan Sistem

2017 ◽  
Vol 1 (2) ◽  
pp. 211-224
Author(s):  
Ezhari Asfa’ani
Keyword(s):  
Quadratic Differential ◽  
Information Structure ◽  
Nash Equilibria ◽  
Sufficient Conditions ◽  
Planning Horizon ◽  
Open Loop ◽  
Linear Quadratic ◽  
Linear Quadratic Differential Games ◽  
Necessary And Sufficient ◽  
Infinite Planning Horizon

We discuss about Nash equilibria for the linear quadratic differential game for an infinite planning horizon. We consider an open-loop information structure. In the standard literature this problem is solved under the assumption and provide both necessary and sufficient conditions for existence of Nash equilibria for this game under the assumption that the system as a whole is stabilizable.      Keywords: linear quadratic differential games, open-loop information structure

On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems

2020 ◽  
Vol 26 ◽  
pp. 41
Author(s):  
Tianxiao Wang
Keyword(s):  
Optimal Control ◽  
Closed Loop ◽  
Optimal Control Problems ◽  
Mean Field ◽  
Open Loop ◽  
Time Inconsistency ◽  
Control Problems ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Equilibrium Strategies

This article is concerned with linear quadratic optimal control problems of mean-field stochastic differential equations (MF-SDE) with deterministic coefficients. To treat the time inconsistency of the optimal control problems, linear closed-loop equilibrium strategies are introduced and characterized by variational approach. Our developed methodology drops the delicate convergence procedures in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. When the MF-SDE reduces to SDE, our Riccati system coincides with the analogue in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. However, these two systems are in general different from each other due to the conditional mean-field terms in the MF-SDE. Eventually, the comparisons with pre-committed optimal strategies, open-loop equilibrium strategies are given in details.

Berge and Nash Equilibria in a Linear-Quadratic Differential Game

2020 ◽  
Vol 81 (11) ◽  
pp. 2108-2131
Author(s):  
V. I. Zhukovskiy ◽  
A. S. Gorbatov ◽  
K. N. Kudryavtsev
Keyword(s):  
Differential Game ◽  
Quadratic Differential ◽  
Nash Equilibria ◽  
Linear Quadratic

scholarly journals Modified LQG/LTR Control Methodology in Active Structural Control

2003 ◽  
Vol 22 (2) ◽  
pp. 97-108 ◽  
Author(s):  
Yan Sheng ◽  
Chao Wang ◽  
Ying Pan ◽  
Xinhua Zhang
Keyword(s):  
Structural Control ◽  
Signal To Noise Ratio ◽  
Open Loop ◽  
Control Force ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Control Approach ◽  
Active Structural Control ◽  
Loop Transfer Recovery ◽  
Control Methodology

This paper presents a new active structural control design methodology comparing the conventional linear-quadratic-Gaussian synthesis with a loop-transfer-recovery (LQG/LTR) control approach for structures subjected to ground excitations. It results in an open-loop stable controller. Also the closed-loop stability can be guaranteed. More importantly, the value of the controller's gain required for a given degree of LTR is orders of magnitude less than what is required in the conventional LQG/LTR approach. Additionally, for the same value of gain, the proposed controller achieves a much better degree of recovery than the LQG/LTR-based controller. Once this controller is obtained, the problems of control force saturation are either eliminated or at least dampened, and the controller band-width is reduced and consequently the control signal to noise ratio at the input point of the dynamic system is increased. Finally, numerical examples illustrate the above advantages.

scholarly journals Backward-forward linear-quadratic mean-field Stackelberg games

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Kehan Si ◽  
Zhen Wu
Keyword(s):  
Large Population ◽  
Consistency Condition ◽  
Market Price ◽  
Mean Field ◽  
Mapping Method ◽  
Open Loop ◽  
Stackelberg Games ◽  
Linear Quadratic ◽  
Population System ◽  
The Cost

AbstractThis paper studies a controlled backward-forward linear-quadratic-Gaussian (LQG) large population system in Stackelberg games. The leader agent is of backward state and follower agents are of forward state. The leader agent is dominating as its state enters those of follower agents. On the other hand, the state-average of all follower agents affects the cost functional of the leader agent. In reality, the leader and the followers may represent two typical types of participants involved in market price formation: the supplier and producers. This differs from standard MFG literature and is mainly due to the Stackelberg structure here. By variational analysis, the consistency condition system can be represented by some fully-coupled backward-forward stochastic differential equations (BFSDEs) with high dimensional block structure in an open-loop sense. Next, we discuss the well-posedness of such a BFSDE system by virtue of the contraction mapping method. Consequently, we obtain the decentralized strategies for the leader and follower agents which are proved to satisfy the ε-Nash equilibrium property.

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