Showing papers on "Stackelberg competition published in 1977"
31 citations
TL;DR: The Nash solution is desirable only if it is not dominated by any of the Stackelberg solutions and, as the Nash solution, it can be enforced once an agreement between the players, specifying the leader and the follower, is reached.
22 citations
TL;DR: Using dynamic programming, feedback Stackelberg strategies for the general linear quadratic discrete-time game were derived in this paper, where the game was formulated as a convex combinatorial game.
Abstract: Using dynamic programming, feedback Stackelberg strategies are derived for the general linear quadratic discrete-time game.
15 citations
5 citations
01 Dec 1977
TL;DR: In this paper, the authors consider a multicontrollers problem where the information flow is restricted by constraining it to be in the form of sampled data acquisition, and obtain a solution which maintains the computational simplicity of the tractable open loop solution while gaining the responsiveness of a state feedback solution, avoiding the complications of the purely closed loop formulation.
Abstract: In this paper we consider a multicontroller problem in which each control agent has a different objective function. The actions of the controllers are coordinated by the influence of one controller who plays according to a Stackelberg strategy relative to the remaining players. We investigate this formulation when the information flow is restricted by constraining it to be in the form of sampled data acquisition. The computational advantage of the sampled data formulation is quite significant. Of equal importance is the relationship among the sampled data, closed loop and open loop solutions. The existence of and solution for the closed loop Stackelberg solution for the continuous time game are, at present, unresolved problems. The primary motivation for considering the sampled data formulation is to obtain a solution which maintains the computational simplicity of the tractable open loop solution while gaining the responsiveness of a state feedback solution, avoiding the complications of the purely closed loop formulation. The linear quadratic problem is considered in detail and an efficient solution algorithm is derived which takes advantage of certain characteristics of the sampled data solution.
1 citations
01 Dec 1977
TL;DR: The closed-loop Stackelberg solution as mentioned in this paper is a class of hierarchical optimization problems with different objectives for each level, and it is known as the Stackeberg solution.
Abstract: This paper discusses properties of solutions to a class of hierarchical optimization problems with different objectives for each level. The solution of these problems is known as the closed-loop Stackelberg solution. Two simple examples are solved to illustrate a fundametal non-convexity in the formulation of the optimization problem, and to highlight the dominant properties of the solutions.
TL;DR: In this paper, a mathematical theorem which applies to all conjectural variation models of markets involving profit maximizing firms including monopoly and perfect competition as well as oligopoly is presented, and the theorem is proved to be applicable to all variants of the market.
Abstract: The proposition embodied in the title is a mathematical theorem which applies to all conjectural variation models of markets involving profit maximizing firms including monopoly and perfect competition as well as oligopoly. The intractability of the oligopoly market has long been lamented and the "heroic" simplifying assumptions of Cournot, Bertrand, von Stackelberg and Sweezy have not provided an entirely satisfactory solution. The new approaches of Bain and Sylos-Labini have been fruitful as empirical formulations but the theoretical results in oli-
01 Dec 1977
TL;DR: The Stackelberg approach of game theory is considered for the optimization of dynamic systems upon which control action is exerted at two different levels.
Abstract: In this paper, we study some aspects of performance optimization of dynamic systems upon which control action is exerted at two different levels. The system considered is composed of N subsystems each controlled by a local controller and a central controller. The objective function of each local controller assesses the performance of the corresponding subsystem, and the objective function of the central controller assesses the performance of the overall system. Such optimization problems often arize in practice, such as in many computer-controlled engineering processes, economic systems and power networks. In this paper the Stackelberg approach of game theory is considered for the optimization of such systems.