In large scale networks users often behave selfishly trying to minimize their routing cost. Modelling this as a noncooperative game, may yield a Nash equilibrium with unboundedly poor network performance. To measure this inefficacy, the Coordination Ratio or Price of Anarchy (PoA) was introduced. It equals the ratio of the cost induced by the worst Nash equilibrium, to the corresponding one ind...

In this paper, we try to design a service mechanism for profit optimizations of both a cloud provider and its multiple users. We consider the problem from a game theoretic perspective and characterize the relationship between the cloud provider and its multiple users as a Stackelberg game, in which the strategies of all users are subject to that of the cloud provider. The cloud provider tries t...

Abstract: The report evolves a method, which uses the formalization and results of positional antagonistic dierential games theory, developed by N. N. Krasovskii and his scienti c school, for constructing solutions of a class of non-antagonistic dierential games. The method transforms non-antagonistic game into so-called non-standard optimal control problem. Numerical solutions for Stackelberg ...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

Coopetition means that in economic interactions, both competition and cooperation are presented the same time. We built investigated analytically numerically game theoretic models of coopetition normal form characteristic function. The basic model reflects between firms Cournot oligopoly their mutually profitable activities such as marketing, R&D, environmental protection. Each firm divides...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

While three deployed applications of game theory for security have recently been reported, we as a community of agents and AI researchers remain in the early stages of these deployments; there is a continuing need to understand the core principles for innovative security applications of game theory. Towards that end, this paper presents PROTECT, a gametheoretic system deployed by the United Sta...

This paper studies a class of dynamic Stackelberg games under open-loop information structure with constrained linear agent dynamics and quadratic utility functions. We show two important properties for this class of dynamic Stackelberg games. First, we prove that under mild conditions, the optimal control of individual agents at the solution of the Stackelberg game coincides with the solution ...

With the increasing demands of consumers for product grade, C2B model high-grade e-commerce emerges as required. In order to solve problem coordination and cooperation between platforms manufacturers, further develop e-commerce, this paper studies supply chain interests by establishing a differential game considering grade factors. By comparing equilibrium solutions games under different decisi...

In a vendor-managed inventory (VMI) system, manufacturing vendor manages their retailer inventories. Studies on VMI-type supply chains mostly have not considered competition between retailers. There are few works the price competition; however, to best of authors’ knowledge, none papers formulated service strategy. The level is one competitive factors among competing Sometimes retailers choose ...