Complete Information Static Game Research Articles

Formation mechanism of on-grid power tariff using game model of complete information

The key to the reform of the power system is to design a fair bidding and trading system. Analyzing the transaction process of electricity price competition, suppressing market power and other unfavorable factors, and finding a perfect bidding system are the research goals of this paper. In order to study the competition in the power spot market and power contract market, this paper employs the game model of complete information and the game theory as a tool. The power spot market adopts the Market Clearing Price (MCP) settlement method, in which the power grid determines the maximal real-time price of the generator node as the MCP. The price is based on the three bidding strategy curves of the power plant. As a result, a Nash equilibrium of power plant revenue is formed. According to the Cournot model and Stackelberg model that analyze the power contract market, the long-term equilibrium price of Stackelberg model in the power contract market is higher than that of the perfectly competitive market and less than or equal to the output of perfect monopoly market. The long-term equilibrium price and output in the power contract market are both certain and stable. This paper has analyzed the static game of complete information in the power market and carried out practical application. The results show that the bidding strategies of power plants have a Nash equilibrium and they have an incentive to collude. The MCP mechanism cannot solve the problem of market power influence. The conclusion of the research provides a basis for the design of the power hybrid auction system.

A Game Model for Analyzing Wireless Sensor Networks of 5G Environment Based on Adaptive Equilibrium Optimizer Algorithm.

Wireless sensors networks (WSNs) play an important role in life. With the development of 5G, its security issues have also raised concerns. Therefore, it is an important topic to study the offense and defense confrontation in WSNs. A complete information static game model is established to analyze the offense and defense confrontation problem of WSNs in 5G. An adaptive equilibrium optimizer algorithm (AEO) based on parameter adaptive strategy is proposed, which can jump out of the local optimal solution better. Experiments show that the optimization ability of AEO outperforms other algorithms on at least 80% of the 23 classical test functions of CEC. The convergence speed of AEO is better in the early stage of population iteration. The optimal offensive and defensive strategy under different offense and defense resources through simulation experiments is analyzed. The conclusion shows that when the offensive resources are large, the offender takes an indiscriminate attack. When the defense resources are small, the defender should defend the most important elements, and when the defense resources are large, the defender should allocate the same resources to defend each element to obtain the maximum benefit. This paper provides new solution ideas for the security problems under the offense and defense game in WSNs.

A Tri-dimensional Equilibrium-based stochastic optimal dispatching model for a novel virtual power plant incorporating carbon Capture, Power-to-Gas and electric vehicle aggregator

This study proposes a novel structure of carbon-to-power-based virtual power plant (C2P-VPP) considering the flexible demand response and electric vehicle-to-grid aggregators (EVA). C2P is integrated by gas-power plant carbon capture (GPPCC), carbon storage devices (CS), and power-to-gas (P2G). Then, to balance the multiple objectives of the dispatching cost, the carbon emission and the output fluctuation, a tri-dimensional coordinated optimal dispatching model is construct from the perspective of the energy impossibility triangle problem. And the robust optimization theory is applied to characterize the uncertainty of wind power plant (WPP) and photovoltaic power generation (PV). Thirdly, to solve the above multi-objective model, an improved fuzzy equilibrium coordination-based-model solution algorithm is proposed. The algorithm integrates the fuzzy satisfaction theory, the multi-objective input income table, the entropy weight method into the complete information static game model. Finally, the CIGRE medium voltage distribution system is chosen for case study, the results show: (1) GPPCC could capture and store CO2 in carbon storage devices, and P2G could convert the CO2 into CH4 for conventional gas turbines (CGT) providing flexible power output. Compared with the scenario only with CS or P2G, when they are both introduced, the carbon emissions reduced by 7.75 % and 3.82 %, the dispatching cost reduced by 2.90 % and 7.77 %, and the output fluctuation reduced by 10.03 % and 2.80 %. (2) When robust coefficient Г is from 0.85 to 0.95, the decision-maker is the risk preference type and willing to bear risk to pursue excess benefit. (3) Sensitivity analysis shows when the rated capacity ratio of CGT, GPPCC and P2G is from 8:4:1 to 2:2:1, the dispatching scheme are optimal. When the capacity ratio of WPP, PV and EVA is from 20:1 to 10:1, the objective value changes significantly, and the optimal equilibrium scheme could be established when the capacity ratio is higher than 10:1. Therefore, the proposed optimal dispatching model could provide an effective tools for decision makers to achieve the optimal dispatching schemes.

Optimisation of group batch scheduling in flexible flow shop based on multi-player cooperative game

In a flexible flow shop, if there are group batch processes, the processing task needs to form multiple batches for production in the batch operation. In order to make up batch processing, there will be job-waiting time thereby extending the total working hours of the production process, and the conflict between various production indexes is further intensified. Therefore, this paper first establishes the group batch scheduling of flexible flow shop (GBSFFS) mathematical model, and proposes a local scheduling method based on multi-player cooperation and complete information static game, establishes a method of game elements such as game information, game player, game strategy, game payoff for group batch processing, and uses the method for behaviour prediction of various game players, that is, the valuation indexes, which reduce the evaluation indexes conflict in the GBSFFS problem. On the premise of reducing the waiting time, other evaluation indexes have been increased.

On-ramp merging strategy for connected and automated vehicles based on complete information static game

Improper handling of vehicle on-ramp merging may hinder traffic flow and contribute to lower fuel economy, while also increasing the risk of collisions. Cooperative control for connected and automated vehicles (CAVs) has the potential to significantly reduce negative environmental impact while also improve driving safety and traffic efficiency. Therefore, in this paper, we focus on the scenario of CAVs on-ramp merging and propose a centralized control method. Merging sequence (MS) allocation and motion planning are two key issues in this process. To deal with these problems, we first propose an MS allocation method based on a complete information static game whereby the mixed-strategy Nash equilibrium is calculated for an individual vehicle to select its strategy. The on-ramp merging problem is then formulated as a bi-objective (total fuel consumption and total travel time) optimization problem, to which optimal control based on Pontryagin's minimum principle (PMP) is applied to solve the motion planning issue. To determine the proper parameters in the bi-objective optimization problem, a varying-scale grid search method is proposed to explore possible solutions at different scales. In this method, an improved quicksort algorithm is designed to search for the Pareto front, and the (approximately) unbiased Pareto solution for the bi-objective optimization problem is finally determined as the optimal solution. The proposed on-ramp merging strategy is validated via numerical simulation, and comparison with other strategies demonstrates its effectiveness in terms of fuel economy and traffic efficiency. • MS allocation is modeled as a two-player game, where Pontryagin's minimum principle is used for control law calculation. • Illustrating in detail mixed-strategy Nash equilibrium of the game for MS allocation. • Proposing a varying-scale grid search algorithm to search for candidated parameters in the cost function.

Research on Attack and Defense Game Model for Improving the Efficiency of Network Intrusion Detection System

The widespread use of wireless networks has expanded people’s ability to obtain information, but its inherent network characteristics make it more vulnerable to cyber-attacks. Existing intrusion detection systems usually only target specific attack methods, but are incapable of other attacks. Based on this research background, taking game theory as the theoretical basis, it analyses the offensive and defensive process in wireless sensor networks, and demonstrates the necessity of implementing an intrusion detection system by analysing model equilibrium solutions. In view of the diversity of attack methods of network intruders, the game model is further improved, and a non-cooperative complete information static game model is established. By analysing the mixed Nash equilibrium solution of the model, the best defines strategy of the intrusion detection system is obtained and the system is balanced. Energy consumption and detection efficiency. Simulation experiment results show that the wireless sensor network intrusion detection system based on offensive and defensive game can not only effectively resist multiple network attacks, but also reduce the energy consumption caused by the intrusion detection system and prolong the service life of the network.

CAN MANDATORY DIVIDEND POLICY REDUCE THE AGENCY COST OF LISTED COMPANIES? MODEL ANALYSIS AND EMPIRICAL TEST IN CHINA

In this research, the mixed strategy complete information static game was adopted to explain the effect of mandatory dividend policy on agency cost, and Chinese mandatory dividend policy introduced in 2011was regarded as the institutional background, and whether mandatory dividend policy can reduce the agency cost of listed companies as an accidental impact was studied. Empirical test indicates that mandatory dividend policy significantly inhibits the agency cost of enterprises. Further research finds that the mandatory dividend policy has a better effect on reducing agency costs for the companies listed on the main board and those with normal dividends, while it has no significant effect on restraining agency costs for the companies with micro-dividends and small and medium-sized boards. The study supports the dividend agency cost theory and provides empirical evidence for the regulating departments to improve the follow-up policy of capital market governance.

Study on the Attacking Intelligent Decision-Making Technology Based on the Game Theory

This paper focuses on the game decision-making technology for the multi-agent confrontational environment. A new mission decision-making method of multi-agent cooperative attack on the multi-object is elaborated based on two-person non-cooperative complete information static game model. The proposed method is implemented into the intelligent decision-making technology for the two sides’ attack via the Nash equilibrium optimization. A case study is analyzed, which results illustrate that this method can realize the intelligent forecasting and multi-agent decision-making, as well as confirm the feasibility of this technology in the confrontational intelligent decision-making.

Nonparametric identification of the distribution of random coefficients in binary response static games of complete information

This paper studies binary response static games of complete information allowing complex heterogeneity through a random coefficients specification. The main result of the paper establishes nonparametric point identification of the joint density of all random coefficients except those on interaction effects. Under additional independence assumptions, we identify the joint density of the interaction coefficients. Moreover, we prove that in the presence of covariates that are common to both players, the player-specific coefficient densities are identified, while the joint density of all random coefficients is not point-identified. However, we do provide bounds on counterfactual probabilities that involve this joint density.

The Game Relationship Between Government and Individual in China Rural Endowment Insurance

With the aging problem aggravated gradually, the pension problem has aroused the concern of many scholars and it become a very unique social problem in china. In the future development, the way to solve the aging problem will be largely through the way of pension insurance. Based on the large difference in China region, this paper chooses the rural areas with more serious aging problems, and uses the game theory to establish the complete information static game to discuss the game relationship between the government and the individual in the rural endowment insurance. Finally, on the basis of certain assumptions, a complete information static game model of government and individual in rural endowment insurance is established, and this paper solve the Nash equilibrium (solution) and utility of the game model in the range of ZZ (the government's profit value when the government chooses to provide the strategy) and the GG (personal benefit value of the individual's choice of payment strategy). Finally, this paper discusses the assumptions and gives the prospect to the further development of the model.

Research of Complete Information Static Game Model for Software Manufacturer, White Hats and Black Hats

Aiming at the problem of strategy selection in medium-sized software manfacturer’s public test service, we proposed a research method which based on the complete information static game model between software manufacturers, white hats and black hats. Firstly, we study the strategy selection and function of the software manufacturer, and provide one relational expression between the credibility of white hat and software information given by the software manufacturer. Then, we study the information theft of black hat, and provide the other relational expression between the time of information theft and the time of vulnerability exploiting. According to the time of vulnerability repair used by software manufacturer and the time of successful vulnerability attack used by black hat, we provide a method of software vulnerability risk level assessment. Finally, we give an example to show that this model can provide a good strategy for software manufacturers to reduce the risk level of software vulnerabilities.

Research on Subsidy Strategy of Mobike Based on Complete Information Static Game

This paper take Intelligent sharing bicycle company Mobike for example, first introduce the current situation of Mobike, then establishes a complete information static game model for the fixed amount subsidy strategy and the fixed proportion subsidy strategy, and analyzes its strategic equilibrium solution and reasonable price range, get conclusion that Mobike company expand the market share through the subsidy in the short term, but it cannot be maintained for a long time and needs diversification the profitability approach.

Optimal joint control and triggering strategies against denial of service attacks: a zero‐sum game

This study is concerned with the optimal control and scheduling problem for linear networked control systems with communication constraints and security issues. The communication channel, which connects remote sensors with a controller, has limited transmission capability and may suffer denial of service attacks from an external attacker. Unlike most existing cyber-attack-related literature which presumed a prior well-designed control or estimating strategy on which triggering and jamming strategies were established, in the present work, optimal strategies of the controller, the trigger as well as the external attacker are considered simultaneously under the renowned linear quadratic criteria. A designer, who can jointly devise the controller and the trigger, aims to improve the system's performance while the attacker's goal is just the opposite. With the assumption that the trigger and the attacker have limited opportunities to send or attack, a zero-sum static game of complete information is first utilised to investigate the optimal strategies for both players, i.e. the designer and the attacker. The existence of Nash equilibrium (NE) point, i.e. the combination of optimal strategy for each player, is proven afterwards. Finally, the property of none pure-strategy NE in a special case is provided with rigorous proofs. A numerical example is employed to demonstrate how to derive the optimal strategies for the designer and the attacker.

Extensive Game of Horse Race: A Research on <i>Tian Ji's Horse Race</i> Based on Static Games of Complete Information

There are many ways to develop of the classical problem about Tian Ji's Horse Race so that this problem may be researched deeply using theory of games. Therefore, this paper designs n-order extensive game of horse race by changing a rule of traditional problem. After analysis, this paper holds a belief that this game is a kind of static games of complete information, which means theory of static games of complete information can be used to research Tian Ji's Horse Race . With showing all of the strategy profiles of third-order extensive game of horse race and calculating Nash equilibrium of this game, this paper finds some characteristics of the strategy profiles and Nash equilibrium of extensive game of horse race and give the expression of Nash equilibrium of mixed strategy of this game. A new concept of layout is introduced to reveal how strategy profiles influence the outcome of this game. Then the characteristic of the layouts of extensive game of horse race and the layout that can make Tian Ji’s payoff biggest are found and proved, which is drawn from the result of some simulations about fourth-order and fifth-rank extensive games of horse race using a Java program.

Externality of Internet Companies' Scientific and Technological Innovation in the Complete Information Static Game

The purpose of this study was to explore in Internet industry whether a company’s R&D choice is affected by other companies’ choices and point out the scope it matters, futher, determine the best R&D strategy on different occasions. The paper established a rectified Cournot model. Based on the traditional model, the paper added two parameters: knowledge spillover effect and knowledge absorptive capacity. The paper argues that the externality of R&D doesn’t exist when the above parameters changes within a certain range. Thus, the paper put forward that the government should strengthen patent protection and supply financial support to encourage R&D. This study innovatively applied rectified Cournot model, and discussed R&D from the microscopic perspective.

A Game Theoretic Study of Enterprise Mergers and Acquisitions: The Case of RJR Nabisco Being Acquired by KKR

There are both macro- and micro-level studies concerning enterprise mergers and acquisitions (M&A). Past studies have focused on M&A valuation, utility of the M&A motives and the strategic behavior during of the M&A process. Few game theory methods in the application of M&A stay mostly in the analysis of Nash equilibrium under the complete information static game. This paper thus aims to analyze the M&A behavior of enterprises within the framework of incomplete information dynamic game, combined with sub-game perfect Nash equilibrium of complete information dynamic game and Bayesian Nash equilibrium of incomplete information.

Game-based strategy for load service entity to level Duck Chart as well as gain EV consumers

Summary With the increasing penetration of unregulated solar energy, a load service entity (LSE) can exert an externality cost to guide the charging behaviors of electric vehicle (EV) users and level the Duck Chart. This paper introduces a dynamic Stackelberg game model between LSE and EV users to analyze consumer behavior, and a complete information static game model to help LSEs increase profits by gaining share of the EV market. These dynamic and static game models are incorporated into a novel theoretic algorithm with mixed integer programming. A case study shows that the models and the proposed algorithm can level the Duck Chart and guarantee an LSE's share of the EV market. Copyright © 2016 John Wiley & Sons, Ltd.

How to Enhance Employee Voice Behavior Based on Game Theory

With the need of enterprise competition and development, the importance of the employee voice behavior is becoming increasingly apparent. Therefore, people pay more and more attention to employee voice behavior in the field of organization behavior. From the perspective of game theory, this paper has established a static game of complete information and analyzed the strategy selection between enterprise and the employee. Meanwhile, we take appropriate measures in order to achieve win-win development of enterprises and employees.

Researches on Data Privacy in Cloud Computing Based on Game Theory

Existing proposals for data privacy in cloud computing have typically been founded on encryption and are not well-balanced on dealing with the contradiction between data privacy and efficient queries. This paper discusses the data privacy in cloud computing based on the perspective of game theory. It built a complete information static game theory frame between a trusted data center and many un-trusted database service providers to avoid the coalition among un-trusted database service providers, and gave Nash equilibrium of mixed strategy. Some influence factors of Nash equilibrium are also analyzed.

The Second-Degree Price Discrimination of m Firms with n Demand Intervals Pricing Based on Cournot Model

Under the condition of linear demand function, the distribution law of equilibrium segment points of firms enforcing second-degree price discrimination to maximize respective revenues is analyzed in the case of m firms with n intervals pricing by using complete information static game theory. This is a promotion for two firms pricing with n segment intervals and m firms pricing with two segment intervals. The results show that: when m firms divide demand to enforce second-degree price discrimination, the necessary condition of revenue maximization is to divide demand into some intervals and let the length of each interval become geometric series, whose common ratio is 1 / m. The unified formula of equilibrium production, equilibrium price and market equilibrium total revenue of all four kinds of markets under the condition of second-degree price discrimination are presented in the most general sense, further more, the nature of which are analyzed in detail.