Dynamic SPICE-model of resource allocation in marketing networks

We consider a dynamic Stackelberg game theoretic model of the coordination of social and private interests (SPICE-model) of resource allocation in marketing networks. The dynamics of controlled system describes an interaction of the members of a target audience (basic agents) that leads to a change of their opinions (cost of buying the goods and services of firms competing on a market). An interaction of the firms (influence agents) is formalized as their differential game in strategic form. The payoff functional of each firm includes two terms: the summary opinion of the basic agents with consideration of their marketing costs (a common interest of all firms), and the income from investments in a private activity. The latter income is described by a linear function. The firms exert their influence not to all basic agents but only to the members of strong subgroups of the influence digraph (opinion leaders). The opinion leaders determine the stable final opinions of all members of the target audience. A coordinating principal determines the firms' marketing budgets and maximizes the summary opinion of the basic agents with consideration of the allocated resources. The Nash equilibrium in the game of influence agents and the Stackelberg equilibrium in a general hierarchical game of the principal with them are found. It is proved that the value of opinion of a basic agent is the same for all influence agents and the principal. It is also proved that the influence agents assign less resources for the marketing efforts than the principal would like.

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Game-Theoretic Patrolling with Dynamic Execution Uncertainty and a Case Study on a Real Transit System

Journal of Artificial Intelligence Research ◽

10.1613/jair.4317 ◽

2014 ◽

Vol 50 ◽

pp. 321-367 ◽

Cited By ~ 29

Author(s):

F.M. Delle Fave ◽

A.X. Jiang ◽

Z. Yin ◽

C. Zhang ◽

M. Tambe ◽

...

Keyword(s):

Resource Allocation ◽

Los Angeles ◽

Stackelberg Game ◽

Research Area ◽

Stackelberg Equilibrium ◽

Multi Agent Systems ◽

Transit System ◽

Markov Decision ◽

Important Research Area ◽

Dynamic Execution

Attacker-Defender Stackelberg security games (SSGs) have emerged as an important research area in multi-agent systems. However, existing SSGs models yield fixed, static, schedules which fail in dynamic domains where defenders face execution uncertainty, i.e., in domains where defenders may face unanticipated disruptions of their schedules. A concrete example is an application involving checking fares on trains, where a defender's schedule is frequently interrupted by fare evaders, making static schedules useless. To address this shortcoming, this paper provides four main contributions. First, we present a novel general Bayesian Stackelberg game model for security resource allocation in dynamic uncertain domains. In this new model, execution uncertainty is handled by using a Markov decision process (MDP) for generating defender policies. Second, we study the problem of computing a Stackelberg equilibrium for this game and exploit problem structure to reduce it to a polynomial-sized optimization problem. Shifting to evaluation, our third contribution shows, in simulation, that our MDP-based policies overcome the failures of previous SSG algorithms. In so doing, we can now build a complete system, that enables handling of schedule interruptions and, consequently, to conduct some of the first controlled experiments on SSGs in the field. Hence, as our final contribution, we present results from a real-world experiment on Metro trains in Los Angeles validating our MDP-based model, and most importantly, concretely measuring the benefits of SSGs for security resource allocation.

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Cloud Provider's Response to Multiple Models of Attack Behaviors

Recent Patents on Engineering ◽

10.2174/1872212112666180918165944 ◽

2019 ◽

Vol 13 (4) ◽

pp. 325-333

Author(s):

Xu Liu ◽

Xiaoqiang Di ◽

Jinqing Li ◽

Huamin Yang ◽

Ligang Cong ◽

...

Keyword(s):

Stackelberg Game ◽

Multiple Models ◽

Theoretic Model ◽

Cloud Provider ◽

Game Model ◽

Attack Behavior ◽

Behavior Model ◽

Protection Strategy ◽

Behavior Models ◽

Optimal Protection

Background: User behavior models have been widely used to simulate attack behaviors in the security domain. We revised all patents related to response to attack behavior models. How to decide the protected target against multiple models of attack behaviors is studied. Methods: We utilize one perfect rational and three bounded rational behavior models to simulate attack behaviors in cloud computing, and then investigate cloud provider’s response based on Stackelberg game. The cloud provider plays the role of defender and it is assumed to be intelligent enough to predict the attack behavior model. Based on the prediction accuracy, two schemes are built in two situations. Results: If the defender can predict the attack behavior model accurately, a single-objective game model is built to find the optimal protection strategy; otherwise, a multi-objective game model is built to find the optimal protection strategy. Conclusion: The numerical results prove that the game theoretic model performs better in the corresponding situation.

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The Role of the Business Sector in Global Health Politics

The Oxford Handbook of Global Health Politics ◽

10.1093/oxfordhb/9780190456818.013.23 ◽

2018 ◽

pp. 385-408

Author(s):

Kelley Lee ◽

Julia Smith

Keyword(s):

Collective Action ◽

Global Health ◽

Business Sector ◽

Policy Debate ◽

Public And Private ◽

Health Politics ◽

For Profit ◽

Goods And Services ◽

Private Interests ◽

Health Related

The influence of for-profit businesses in collective action across countries to protect and promote population health dates from the first International Sanitary Conferences of the nineteenth century. The restructuring of the world economy since the late twentieth century and the growth of large transnational corporations have led the business sector to become a key feature of global health politics. The business sector has subsequently moved from being a commercial producer of health-related goods and services, contractor, and charitable donor, to being a major shaper of, and even participant in, global health policymaking bodies. This chapter discusses three sites where this has occurred: collective action to regulate health-harming industries, activities to provide for public interest needs, and participation in decision-making within global health institutions. These changing forms of engagement by the business sector have elicited scholarly and policy debate regarding the appropriate relationship between public and private interests in global health.

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Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information

Applied Sciences ◽

10.3390/app10051557 ◽

2020 ◽

Vol 10 (5) ◽

pp. 1557

Author(s):

Weijia Feng ◽

Xiaohui Li

Keyword(s):

Resource Allocation ◽

Incomplete Information ◽

Stackelberg Game ◽

Superior Performance ◽

Channel Gain ◽

Mobile Users ◽

Pricing Strategies ◽

Game Equilibrium ◽

Allocation Process ◽

Realistic Situation

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.

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Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽

10.3390/en12020325 ◽

2019 ◽

Vol 12 (2) ◽

pp. 325 ◽

Cited By ~ 2

Author(s):

Shijun Chen ◽

Huwei Chen ◽

Shanhe Jiang

Keyword(s):

Electric Vehicles ◽

Heterogeneous Networks ◽

Demand Uncertainty ◽

Stackelberg Game ◽

Optimal Solution ◽

Stackelberg Equilibrium ◽

Optimal Decision ◽

Charging Station ◽

Simulation Results ◽

Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

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