Stackelberg competition

About: Stackelberg competition is a research topic. Over the lifetime, 6611 publications have been published within this topic receiving 109213 citations.

Stable cartels with a Cournot fringe

Abstract: The notion of an industry structure characterized by a small group of dominant firms plus a competitive fringe has a long tradition More recent work explores conditions under which such a pattern constitutes an equilibrium, assuming collusive behavior among one group of firms and price-taking behavior within the fringe [2; 3; 4; 5; 6; 14; 17] The alternative case of a Courot fringe is analyzed briefly in Spulber [22, 471-73] and more extensively in Martin [14] Here we adopt the framework of this literature and build on it by analyzing the size and uniqueness of the stable cartel when the fringe is Coumot; endogeneity of Courot versus Bertrand behavior within the fringe, given the stable cartel; possible endogeneity of the Stackelberg sequence of play between the cartel and the fringe; and effects of excludability from the cartel Welfare effects are also briefly analyzed Alternatively, cooperation within a cartel is equivalent to the outcome of horizontal mergers in the absence of synergies As such, this paper presents a contrasting result to the analysis of exogenous Cournot mergers in Salant, Switzer, and Reynolds [18], endogenizes the merger decision, and demonstrates how a theory of mergers can be predicated on a Cournot fringe

Optimal patrol strategy for protecting moving targets with multiple mobile resources

Abstract: Previous work on Stackelberg Security Games for scheduling security resources has mostly assumed that the targets are stationary relative to the defender and the attacker, leading to discrete game models with finite numbers of pure strategies. This paper in contrast focuses on protecting mobile targets that lead to a continuous set of strategies for the players. The problem is motivated by several real-world domains including protecting ferries with escorts and protecting refugee supply lines. Our contributions include: (i) a new game model for multiple mobile defender resources and moving targets with a discretized strategy space for the defender and a continuous strategy space for the attacker; (ii) an efficient linear-program-based solution that uses a compact representation for the defender's mixed strategy, while accurately modeling the attacker's continuous strategy using a novel sub-interval analysis method; (iii) a heuristic method of equilibrium refinement for improved robustness and (iv) detailed experimental analysis in the ferry protection domain.

Load adaptive pricing: An emerging tool for electric utilities

Abstract: Motivated by the importance of the peak load problem faced by the electric utility industries; in this paper we analyze several different electricity pricing schemes from a game theoretic point of view. Recognizing the limit of the traditional peak load pricing formulation and the persuasive breakthroughs in microelectronic technology, we introduce a philosophy in which supply and demand respond to each other through prices and consumptions, and the utility company sells power at "real-time" rates. We call it load adaptive pricing. By itself, the concept of load adaptive pricing is not new. The contribution of this paper is the formulation and resolution of this idea as a closed-loop dynamic Stackelberg game problem. The central part of this problem is how to choose appropriate incentives (i.e., pricing strategies) so that customers can be induced to behave co-operatively and thus achieve the team optimum. In this paper, the load adaptive pricing problem is solved for a particular producer/consumer model. We demonstrate that it is possible for the utility company to induce the customer to behave cooperatively to achieve the team optimum. We also show that in steady state, our solution converges and the system is stable.

A game theoretic analysis of service competition and pricing in heterogeneous wireless access networks

Abstract: Next generation wireless systems will provide highspeed wireless connectivity and seamless mobility through the provisioning of heterogeneous wireless access. In such a heterogeneous wireless access environment, mobile users will be able to connect to multiple wireless networks (e.g., IEEE 802.16, cellular, and IEEE 802.11-based networks) operated by different service providers, simultaneously. We address the problem of competitive pricing in such a heterogeneous wireless access network. Each of the wireless access networks is assumed to support two types of connections, namely, premium and best-effort connections. For the premium connections, the price is fixed, while for the best effort connections it is dynamic and depends on the competitive or cooperative behavior of the service providers. A competitive pricing model for best-effort connections is developed based on a noncooperative game formulation. We first consider the case where the prices are offered to the users at the same time (i.e., a simultaneous-play game). Nash equilibrium is considered as the solution of this game. Afterwards, we consider the case where a service provider can offer its price before other providers. This is referred to as a leader-follower game for which Stackelberg equilibrium is considered as the solution. We also consider a cooperative pricing model which maximizes the total revenue of the service providers. A method for revenue sharing is presented for this cooperative pricing model. Numerical studies are carried out to evaluate the performances of the different pricing models.

Human-Like Decision Making for Autonomous Driving: A Noncooperative Game Theoretic Approach

Abstract: Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on roads in the future for a long time, how to merge AVs into human drivers’ traffic ecology and minimize the effect of AVs and their misfit with human drivers, are issues worthy of consideration. Moreover, different passengers have different needs for AVs, thus, how to provide personalized choices for different passengers is another issue for AVs. Therefore, a human-like decision making framework is designed for AVs in this paper. Different driving styles and social interaction characteristics are formulated for AVs regarding driving safety, ride comfort and travel efficiency, which are considered in the modeling process of decision making. Then, Nash equilibrium and Stackelberg game theory are applied to the noncooperative decision making. In addition, potential field method and model predictive control (MPC) are combined to deal with the motion prediction and planning for AVs, which provides predicted motion information for the decision-making module. Finally, two typical testing scenarios of lane change, i.e., merging and overtaking, are carried out to evaluate the feasibility and effectiveness of the proposed decision-making framework considering different human-like behaviors. Testing results indicate that both the two game theoretic approaches can provide reasonable human-like decision making for AVs. Compared with the Nash equilibrium approach, under the normal driving style, the cost value of decision making using the Stackelberg game theoretic approach is reduced by over 20%.