Stackelberg competition

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

Stackelberg Leadership as a Natural Solution Under Cost Uncertainty

Abstract: This paper analyzes a differentiated duopoly model with cost uncertainty in an environment where information sharing is prohibited. The duopolists can commit themselves to be a Stackelberg leader or follower at the time when they know the distribution, but not the actual values, of their own and the rival's costs. In a natural Stackelberg situation, the firms agree on the assignment of roles and neither prefers the (Bayesian) Nash equilibrium. An natural Stackelberg situation is shown to be possible under quantity (but not price) competition. Total expected welfare is higher in the natural Stackelberg situation than in the Nash equilibrium. Copyright 1990 by Blackwell Publishing Ltd.

Stackelberg Game for Bandwidth Allocation in Cloud-Based Wireless Live-Streaming Social Networks

Abstract: Multimedia social networks have been introduced as a new technology to enrich people's lives through enhanced multimedia distribution. On the other hand, a media cloud system can perform multimedia processing and storage, and provide heterogeneous multimedia services. However, the challenges still remain for end users (e.g., mobile devices and PCs) to receive multimedia streaming from the cloud system with satisfied quality-of-service (QoS). To address these challenges, an efficient multimedia distribution approach taking advantage of live-streaming social networks is innovated in this paper to deliver the media services from the cloud to both desktop and wireless end users. Our approach allows bandwidth limited mobile users to acquire live multimedia streaming from desktop users, directly based on their social relationships rather than from the cloud. When a number of mobile users compete for limited bandwidth access with the desktop users, a bandwidth allocation problem must be solved to meet all users' QoS requirements in the live-streaming social network. We formulate the problem as a two-stage Stackelberg game, in which both desktop users and mobile users target at maximizing their utilities. In our study, a noncooperative game is used to model the competition among the desktop users in terms of shared bandwidth and price in the first stage of the game. The second stage of the game models the behavior of a mobile user selecting the desktop users by an evolutionary game. In addition, a case study is conducted following the general Stackelberg game formulation, where the existence of a unique Nash equilibrium is proved. Based on our game modeling, we design protocols for both desktop and mobile users and evaluate them with numerical examples.

Stackelberg Strategies and Collusion in Network Games with Splittable Flow

Abstract: We study the impact of collusion in network games with splittable flow and focus on the well established price of anarchy as a measure of this impact. We first investigate symmetric load balancing games and show that the price of anarchy is at most m, where m denotes the number of coalitions. For general networks, we present an instance showing that the price of anarchy is unbounded, even in the case of two coalitions. If latencies are restricted to polynomials with nonnegative coefficients and bounded degree, we prove upper bounds on the price of anarchy for general networks, which improve upon the current best ones except for affine latencies. In light of the negative results even for two coalitions, we analyze the effectiveness of Stackelberg strategies as a means to improve the quality of Nash equilibria. In this setting, an α fraction of the entire demand is first routed centrally by a Stackelberg leader according to a predefined Stackelberg strategy and the remaining demand is then routed selfishly by the coalitions (followers). For a single coalitional follower and parallel arcs, we develop an efficiently computable Stackelberg strategy that reduces the price of anarchy to one. For general networks and a single coalitional follower, we show that a simple strategy, called SCALE, reduces the price of anarchy to 1+α. Finally, we investigate SCALE for multiple coalitional followers, general networks, and affine latencies. We present the first known upper bound on the price of anarchy in this case. Our bound smoothly varies between 1.5 for α=0 and full efficiency for α=1.

Bayesian stackelberg games and their application for security at Los Angeles international airport

Abstract: Many multiagent settings are appropriately modeled as Stackelberg games [Fudenberg and Tirole 1991; Paruchuri et al. 2007], where a leader commits to a strategy first, and then a follower selfishly optimizes its own reward, considering the strategy chosen by the leader. Stackelberg games are commonly used to model attacker-defender scenarios in security domains [Brown et al. 2006] as well as in patrolling [Paruchuri et al. 2007; Paruchuri et al. 2008]. For example, security personnel patrolling an infrastructure commit to a patrolling strategy first, before their adversaries act taking this committed strategy into account. Indeed, Stackelberg games are being used at the Los Angeles International Airport to schedule security checkpoints and canine patrols [Murr 2007; Paruchuri et al. 2008; Pita et al. 2008a]. They could potentially be used in network routing, pricing in transportation systems and many other situations [Korilis et al. 1997; Cardinal et al. 2005]. Although the follower in a Stackelberg game is allowed to observe the leader’s strategy before choosing its own strategy, there is often an advantage for the leader over the case where both players must choose their moves simultaneously. To see the advantage of being the leader in a Stackelberg game, consider the game with the payoff as shown in Table I. The leader is the row player and the follower is the column player. The only pure-strategy Nash equilibrium for this game is when the leader plays a and the follower plays c which gives the leader a payoff of 2. However, if the leader commits to a mixed strategy of playing a and b with equal (0.5) probability, then the follower will play d, leading to an expected payoff for the leader of 3.5.