Incomplete Information Static Game Research Articles

Game-Based Flexible Merging Decision Method for Mixed Traffic of Connected Autonomous Vehicles and Manual Driving Vehicles on Urban Freeways

Connected Autonomous Vehicles (CAVs) have the potential to revolutionize traffic systems by autonomously handling complex maneuvers such as freeway ramp merging. However, the unpredictability of manual-driven vehicles (MDVs) poses a significant challenge. This study introduces a novel decision-making approach that incorporates the uncertainty of MDVs’ driving styles, aiming to enhance merging efficiency and safety. By framing the CAV-MDV interaction as an incomplete information static game, we categorize MDVs’ behaviors using a Gaussian Mixture Model–Support Vector Machine (GMM-SVM) method. The identified driving styles are then integrated into the flexible merging decision process, leveraging the concept of pure-strategy Nash equilibrium to determine optimal merging points and timing. A deep reinforcement learning algorithm is employed to refine CAVs’ control decisions, ensuring efficient right-of-way acquisition. Simulations at both micro and macro levels validate the method’s effectiveness, demonstrating improved merging success rates and overall traffic efficiency without compromising safety. The research contributes to the field by offering a sophisticated merging strategy that respects real-world driving behavior complexity, with potential for practical applications in urban traffic scenarios.

Occlusion-Aware Motion Planning for Autonomous Driving

Motion planning of autonomous vehicles is still challenging in urban road environments with occlusions. In this work, with the view of safety, comfort and efficiency, we present a motion planning framework that enables autonomous vehicles to navigate safely in urban road with occlusions. Our solution mainly includes three parts: local path planning, trajectory planning and speed planning. First, based on the improved Artificial Potential Field to generate the local path, then the optimal trajectory is solved in the S-L coordinate with the local path as the reference line. Finally, the potential risk probability of the occluded area is incorporated into the incomplete information static game framework and implement speed planning based on the game results and the proposed vehicle "safe driving" to complete the collision avoidance between the autonomous vehicle and visible or obscured dynamic traffic participants. Through simulation verification in common traffic scenarios and a comparison with some existing methods, the proposed method is proven to enable autonomous vehicles to navigate safely in traffic scenarios with occlusions and improve the driving efficiency and comfort of autonomous vehicles.

TESTING A CLASS OF SEMI- OR NONPARAMETRIC CONDITIONAL MOMENT RESTRICTION MODELS USING SERIES METHODS

This paper proposes a new test for a class of conditional moment restrictions (CMRs) whose parameterization involves unknown, unrestricted conditional expectation functions. Motivating examples of such CMRs arise from models of discrete choice under uncertainty including certain static games of incomplete information. The proposed test may be viewed as a semi-/nonparametric extension of the Bierens (1982, Journal of Econometrics 20, 105–134) goodness-of-fit test of a parametric model for the conditional mean. Estimating conditional expectations using series methods and employing a Gaussian multiplier bootstrap to obtain critical values, the test is shown to be asymptotically correctly sized and consistent. Simulation studies indicate good finite-sample properties. In an empirical application, the test is used to study the validity of a game-theoretical model for discount store market entry, treating equilibrium beliefs as nonparametric conditional expectations. The test indicates that Walmart and Kmart entry decisions do not result from a static discrete game of incomplete information with linearly specified profits.

Game Theory Analysis of Commercial Banks and Micro-Enterprises Credit in Post - epidemic Era

Micro-Enterprises are an important component of the economy and have made significant contributions to economic development. Especially in the post-epidemic period, the need for national economic growth and the importance of micro-enterprise development is gradually prominent. Micro-Enterprises still face the problem of “financing difficulty”, unable to get enough bank loans. In this paper, from the perspective of game theory, the incomplete information static game between micro-enterprises and commercial banks will be constructed. This paper mainly discusses the pre-loan investigation of commercial banks for micro-enterprises and provides some suggestions for the financing difficulty of micro-enterprises.

The “Surge Phenomenon” of Macro Economy in Developing Countries from the Perspective of Tobacco Economy

Objectives: Starting from the tobacco economy, this paper studies the “surge phenomenon” of macro-economy in developing countries. Methods: This paper studies the impact of tobacco industry on Anhui economy by using the relevant theories of industrial economics, econometrics and regulatory economics, combined with the actual situation of tobacco industry. Based on the analysis of the overall development of tobacco industry, this paper empirically analyzes the relationship between tobacco industry and Anhui economic growth. This paper combs the relevant literature of the existing research results of this theory. Combined with the special fact that government investment accounts for a large proportion in China’s current economic construction, this paper redefines the hypothesis of the investor in the theory of principles. On this basis, the expected equilibrium results of enterprise investment decision-making under government led and market led modes are compared and analyzed by using incomplete information static game model. Results: When the output value of tobacco industry increases by 1%, it will drive the GDP to increase by 0.373%. Secondly, by comparing the economic benefits of tobacco with the social costs of tobacco, it is found that with the economic development, the social costs caused by tobacco increase year by year, but the economic benefits are slightly greater than the social costs. The difference between the two is also increasing year by year. Conclusion: In the context of tobacco control, we should fully consider the advantages and disadvantages of developing the tobacco industry. Under the excessive intervention of the government, the manifestation of the surge phenomenon is more intense, and the final consequence of overcapacity is more serious than that under the market-oriented mode..

A generalized approach to solve perfect Bayesian Nash equilibrium for practical network attack and defense

To address the incomplete information dynamic network attack and defense game in practice, this paper proposes a generalized approach to solve for perfect Bayesian Nash equilibrium (BNE) for practical network attack and defense. To consider “role-shifting” in the practical network attack and defense environment, the proposed approach substitutes solving the Nash equilibrium (NE) problem with a payoff (reward) maximization problem via a profound combination between the subgame perfect NE of the complete information dynamic game and the BNE of the incomplete information static game. Furthermore, to evaluate the effectiveness of the proposed approach, a representative signaling game with specific values is examined from a theoretical perspective. Finally, a real penetration test case targeting a web server is implemented to substantiate the effectiveness of the proposed approach from a practical perspective with some visual verifications and crucial penetration codes, where the attacker successfully obtains the ROOT authority (the highest authority) of the target web server.

An Incomplete Information Static Game Evaluating Community-Based Forest Management in Zagros, Iran

The present study adopts a game theory approach analyzing land-use planning in Zagros forests, Iran. A Static Game of Incomplete Information (SGII) was applied to the evaluation of participatory forest management in the study area. This tool allows a complete assessment of sustainable forest planning producing two modeling scenarios based on (i) high and (ii) low social acceptance. According to the SGII results, the Nash Bayesian Equilibrium (NBE) strategy suggests the importance of landscape protection in forest management. The results of the NBE analytical strategy show that landscape protection with barbed wires is the most used strategy in local forest management. The response to the local community includes cooperation in conditions of high social acceptance and noncooperation in conditions of low social acceptance. Overall, social acceptance is an adaptive goal in forest management plans.

Testing a Class of Semi- or Nonparametric Conditional Moment Restriction Models using Series Methods

This paper proposes a new test for a class of conditional moment restrictions whose parameterization involves unknown, unrestricted conditional expectation functions. Examples of such conditional moment restrictions are conditional mean independence (leading to a nonparametric significance test) and conditional homoskedasticity (with an otherwise unrestricted conditional mean) and also arise from models of single-agent discrete choice under uncertainty and static games of incomplete information. The proposed test may be viewed as a semi-/nonparametric extension of the Bierens (1982) goodness-of-fit test of a parametric model for the conditional mean. Estimating conditional expectations using series methods and employing a Gaussian multiplier bootstrap to obtain critical values, the resulting test is shown to be asymptotically correctly sized and consistent. A simulation study applies the procedure to test the specification of a two-player, binary-action static game of incomplete information, treating equilibrium beliefs as nonparametric conditional expectations.

A Count Data Model with Social Interactions

I present a peer effects model for count data using a static game of incomplete information. I provide sufficient conditions under which the game equilibrium is unique. I estimate the model's parameters using the Nested Partial Likelihood approach and establish asymptotic properties of the estimator. I show that using the standard linear-in-means spatial autoregressive (SAR) model or the SAR Tobit model to estimate peer effects on counting variables generated from the game asymptotically underestimates the peer effects. I use the model to study peer effects on students participation in extracurricular activities, controlling for network endogeneity.

Network Attack and Defense Game Theory Based on Bayes-Nash Equilibrium

In the process of constructing the traditional offensive and defensive game theory model, these are some shortages for considering the dynamic change of security risk problem. By analysing the critical indicators of the incomplete information game theory model, incomplete information attack and defense game theory model and the mathematical engineering method for solving Bayes-Nash equilibrium, the risk-averse income function for information assets is summarized as the problem of maximising the return of the equilibrium point. To obtain the functional relationship between the optimal strategy combination of the offense and defense and the information asset security probability and risk probability. At the same time, the offensive and defensive examples are used to visually analyse and demonstrate the incomplete information game and the Harsanyi conversion method. First, the incomplete information game and the Harsanyi conversion problem is discussed through the attack and defense examples and using the game tree. Then the strategy expression of incomplete information static game and the engineering mathematics method of Bayes-Nash equilibrium are given. After that, it focuses on the offensive and defensive game problem of unsafe information network based on risk aversion. The problem of attack and defense is obtained by the issue of maximizing utility, and then the Bayes-Nash equilibrium of offense and defense game is carried out around the security risk of assets. Finally, the application model in network security penetration and defense is analyzed by designing a simulation example of attack and defense penetration. The analysis results show that the constructed income function model is feasible and practical.

Management of access privileges for dynamic access control

Access control is an important security mechanism for the protection of sensitive information and critical system resources. While it has been well-known that traditional access control models (TACMs), such as DAC, MAC, RBAC, etc., are not well suited for open networks due to the lack of dynamism in the management of access privileges, pro-active or dynamic access control models (PACMs) developed in recent years generally suffer from performance problems due to complex evaluation performed prior to access authorization. In game theory based dynamic access control models, which are one type of dynamic models, each access is modeled as a game that is played between the accessing subject and the accessed or protected object and the result of the play serves as the basis for making the authorization decision. Thus, delay is unavoidably introduced into the authorization process due to such pre-access evaluation. To overcome the shortcomings of TACMs and PACMs simultaneously, in this paper, we propose a new access control model called ISAC that, unlike all present access control models, is used not as a mechanism for access authorization but one for dynamic management of access privileges upon the completion of each access with the result being an updated set of access privileges for the accessing subject and used for updating the corresponding access control list for the subject. Access authorization will still be performed in the same way as that in the traditional access control models. Thus, ISAC offers the advantages of both traditional access control models in performance and pro-active access control models in dynamism. We will apply incomplete information static game to the development of ISAC in which we will show that there exists at least one Bayesian Nash equilibrium for the game play, which is the theoretical foundation for ISAC. We will also describe a framework design and an example implementation to illustrate the application of ISAC to access control. At last, we will present some experimental results to show that while maintaining the effectiveness of dynamic access control through the management of access privileges, ISAC can achieve the performance of traditional access control models.

Task Allocation Without Communication Based on Incomplete Information Game Theory for Multi-robot Systems

In the task allocation of multi-robot system, the communication is an important condition to ensure global consistency. Unfortunately, with the popularity of WLAN, the congestion and interference among the bands are particularly severe, making traditional task allocation methods which rely on communication can not work. In this paper, the task allocation without communication is considered to be an incomplete information game, where game theory is employed to realize the task allocation and cooperation of soccer robots. Firstly, the joint probability distribution of the robot type is established according to the distance information, which can be employed to solve the incomplete information static game. Then the ball velocity information is added to modify the joint probability distribution and the incomplete information dynamic game can be solved in the same way. The experimental results show that the success rate of task allocation without communication can be improved effectively using the proposed method.

Analysis of Core Stakeholder Behaviour in the Tourism Community Using Economic Game Theory

In a Nash equilibrium, every participant's strategy is the optimal reaction to the strategies of others. Based on economic theory, this paper analyses core stakeholders' behaviour in the tourism community at Qingcheng Mountain, Chengdu, China. Taking taxation, land prices and employment as the payoffs, and the local government, the community and the investors as the players, the incomplete information static game model is applied to outline the stakeholders' behaviour. The paper also examines who benefits the most and who occupies a dominant position. The results indicate that the game strategy of residents in Qingcheng Mountain is influenced by the investors. The influence of the investors is also crucial in the decision making mechanism of the tourism community to maintain sustainable tourism development.

Strategic Interaction Model with Censored Strategies

In this paper, we develop a new model of a static game of incomplete information with a large number of players. The model has two key distinguishing features. First, the strategies are subject to threshold effects, and can be interpreted as dependent censored random variables. Second, in contrast to most of the existing literature, our inferential theory relies on a large number of players, rather than a large number of independent repetitions of the same game. We establish existence and uniqueness of the pure strategy equilibrium, and prove that the censored equilibrium strategies satisfy a near-epoch dependence property. We then show that the normal maximum likelihood and least squares estimators of this censored model are consistent and asymptotically normal. Our model can be useful in a wide variety of settings, including investment, R&D, labor supply, and social interaction applications.

The Bidding Strategy Research of Radio Spectrum User Auction Based on the Partial Distribution

In the spectrum auction, bidding strategy of telecommunication operation enterprise is very important. Considing the telecommunication operation enterprise how to choose the optimal bidding strategy as the train of thought. According to the spectrum of value distribution characteristics to the enterprise, using incomplete information static game theory to construct the operating enterprise bidding game model based on the partial distribution, and obtained model’s Nash equilibrium through the simulation with numerical solutions of the form. At the same time, the equilibrium analysis found: enterprise’s valuation central tendency or fluctuation can positive motivate its equilibrium bid; Along with the enterprise central tendency of valuation and fluctuation amplitude of valuation increasing ceaselessly, increasing unit valuation incentive equilibrium bid increment continuously increase.

HOW IMPORTANT ARE ENDOGENOUS PEER EFFECTS IN GROUP LENDING? ESTIMATING A STATIC GAME OF INCOMPLETE INFORMATION

SUMMARYWe quantify the importance of endogenous peer effects in group lending programs by estimating a static game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich dataset from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The preferred model suggests that the probability of a member making a full repayment would be 12 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity. Copyright © 2012 John Wiley & Sons, Ltd.

Clustering routing algorithm of wireless sensor networks based on Bayesian game

To avoid uneven energy consuming in wireless sensor networks, a clustering routing model is proposed based on a Bayesian game. In the model, Harsanyi transformation is introduced to convert a static game of incomplete information to the static game of complete but imperfect information. In addition, the existence of Bayesian nash equilibrium is proved. A clustering routing algorithm is also designed according to the proposed model, both cluster head distribution and residual energy are considered in the design of the algorithm. Simulation results show that the algorithm can balance network load, save energy and prolong network lifetime effectively.

P2P Incentive Mechanism Based on Static Game of Incomplete Information

P2P network is autonomous of sharing file quickly and easily. In recent years, a large number of free-riding nodes and malicious nodes emerge in P2P network, which can’t provide services and have malicious damage to the network system, the result is significant declines of system performance and user satisfaction. In order to solve the problems, a P2P incentive mechanism based on static game of incomplete information is proposed in this paper. The new proposed mechanism has been analyzed and simulated with a series of tests. Experimental results show that the proposed P2P incentive mechanism can solve problem simply and effectively.

The Game Analysis of Rent-Seeking Behavior in the Public Project

Rent-seeking behavior in the public project is a problem which the construction administrative departments at all levels always attach great importance to. This paper analyzed the causes and harms of rent-seeking behavior in the public project. At the same time, according to the hypothesis that supervision department can drive its right impartially, this paper established a tripartite incomplete information static game model in the public project, and then analyzed the own rent-seeking behavior of supervision department, and got the specific measures that could reduce rent-seeking behavior.

How Important Are Endogenous Peer Effects in Group Lending? Estimating a Static Game of Incomplete Information

We quantify the importance of endogenous peer effects in group lending programs by estimating a static game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich data set from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The benchmark model suggests that the probability of a member making a full repayment would be 11 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity.