Effects of information asymmetry on cooperation in the prisoners' dilemma game

Effects of inforination asymmetry on cooperation in the prisoners＇ dilemma game are investigated. The amplitude A is introduced to describe the degree of information asymmetry. It is found that there exists an optimal value of amplitude Aopt at which the fraction of cooperation reaches its maximal value. The reason lies in that cooperators on the two-dimensional grid form large clusters at Aopt. In addition, the theoretical analysis in terms of the mean- field theory is used to understand this kind of phenomenon. It is confirmed that the information asymmetry plays an important role in the dynamics of the dilemma games of spatial prisoners.

Path of the Information Asymmetry of Asset Backed Securitization—Information Game Analysis of Embedded Block Chain Technology

In recent years, the rapid innovation and development of financial industry has made financial enterprises have a lot of information. However, the large amount of information is tampered with and fragmented, which cannot be shared. With the constant innovation of science and technology, it is the most effective way to solve the information lag and asymmetry of financial products. This article aims to start from the problem of asymmetric information of financial products, the analysis of the emerging block chain technology applied in the financial sector, and with the development of asset securitization information known as the typical scenario for the first time, a concrete analysis information game process, and discuss about the application of chain blocks in securitization feasibility.

Value Iteration-Based Cooperative Adaptive Optimal Control for Multi-Player Differential Games With Incomplete Information

This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence proof.The players are divided into two groups in the learning process and adapt their policies sequentially.Our method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based frameworks.Furthermore,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control laws.The efficacy of our method is illustrated by three examples.

On Positional Games With Perfect Information and Their Applications

The game theory was firstly used for description of economic phenomena and social interaction. But there are certain type of perfect information games （PI-games）, the so-called positional game or Banach-Mazur games, which so far have not been applied in economy. The perfect information positional game is defined as the game during which at any time the choice is made by one of the players who is acquainted with the previous decision of his opponent. The game is run on a sequential basis. The aim of this paper is to discuss selected Banach-Mazur games and to present some applications of positional game. This paper also shows new theoretical example of a determined PI-game, based by theoretical overview. All considerations are pure theoretical and based by logical deduction.

Cooperative maneuver decision making for multi-UAV air combat based on incomplete information dynamic game

Cooperative autonomous air combat of multiple unmanned aerial vehicles(UAVs)is one of the main combat modes in future air warfare,which becomes even more complicated with highly changeable situation and uncertain information of the opponents.As such,this paper presents a cooperative decision-making method based on incomplete information dynamic game to generate maneuver strategies for multiple UAVs in air combat.Firstly,a cooperative situation assessment model is presented to measure the overall combat situation.Secondly,an incomplete information dynamic game model is proposed to model the dynamic process of air combat,and a dynamic Bayesian network is designed to infer the tactical intention of the opponent.Then a reinforcement learning framework based on multiagent deep deterministic policy gradient is established to obtain the perfect Bayes-Nash equilibrium solution of the air combat game model.Finally,a series of simulations are conducted to verify the effectiveness of the proposed method,and the simulation results show effective synergies and cooperative tactics.

Bank loan information and information asymmetry in the stock market:evidence from China

In this study,we use bank loan information to construct proxies for corporate transparency and examine whether these measures reflect information asymmetry in the stock market.Our analysis is based on a novel dataset of stock transactions and bank loans of all publicly listed firms on the Shenzhen Stock Exchange,covering January 2008 to June 2013.We find that firms with outstanding loans have a lower level of information asymmetry in the stock market,whereas firms with defaulted loans have a higher level of asymmetry.Further evidence demonstrates that the effect of loan default on information asymmetry in the stock market is more pronounced when these loans are borrowed from joint-equity commercial banks or multiple banks and when the default occurs under inactive market conditions.Our results remain robust to a series of endogeneity and sensitivity tests and provide suggestive evidence of a close connection between the credit loan and stock markets.

Strategy Selection for Moving Target Defense in Incomplete Information Game

As a core component of the network,web applications have become one of the preferred targets for attackers because the static configuration of web applications simplifies the exploitation of vulnerabilities by attackers.Although the moving target defense(MTD)has been proposed to increase the attack difficulty for the attackers,there is no solo approach can cope with different attacks;in addition,it is impossible to implement all these approaches simultaneously due to the resource limitation.Thus,the selection of an optimal defense strategy based on MTD has become the focus of research.In general,the confrontation of two players in the security domain is viewed as a stochastic game,and the reward matrices are known to both players.However,in a real security confrontation,this scenario represents an incomplete information game.Each player can only observe the actions performed by the opponent,and the observed actions are not completely accurate.To accurately describe the attacker’s reward function to reach the Nash equilibrium,this work simulated and updated the strategy selection distribution of the attacker by observing and investigating the strategy selection history of the attacker.Next,the possible rewards of the attacker in each confrontation via the observation matrix were corrected.On this basis,the Nash-Q learning algorithm with reward quantification was proposed to select the optimal strategy.Moreover,the performances of the Minimax-Q learning algorithm and Naive-Q learning algorithm were compared and analyzed in the MTD environment.Finally,the experimental results showed that the strategy selection algorithm can enable defenders to select a more reasonable defensive strategy and achieve the maximum possible reward.

Survey on Resistance Emotion of NCMS in Information Asymmetry and Countermeasures

Through survey on current situation of NCMS construction in Guangxi, we analyze deep reasons for farmers' resistance to NCMS. Major reasons include inadequate propaganda and training effort; narrow compensation scope influencing institutional functions; unreasonable reimbursement mechanism; low level of informatization management; imperfect supervision mechanism; and imperfect laws and regulations. In these situations, we put forward following countermeasures and suggestions: enhance training to ensure working efficiency; expand compensation scope to raise security level; adjust compensation standard to raise reimbursement proportion; lift level of informatization management to reduce costs for institutional operation; strengthen organizational construction to reinforce fund management; open up fund-raising channels to perfect legal system.

Endogenous Explanation for Random Fluctuation of Stock Price and Its Application: Based on the View of Repeated Game with Asymmetric Information

In this paper, we characterize the players’ behavior in the stock market by the repeated game model with asymmetric information. We show that the discount price process of stock is a martingale driven by Brownian motion, and give an endogenous explanation for the random fluctuation of stock price: the randomizations in the market is due to the randomizations in the strategy of the informed player which hopes to avoid revealing his private information. On this basis, through studying the corresponding option pricing problem furtherly, we can give the expression of function φ.

Local mine production safety supervision game analysis based on incomplete information

Utilized fundamental theory and analysis method of Incomplete Information repeated games, introduced Incomplete Information into repeated games, and established two stages dynamic games model of the local authority and the coal mine owner. The analytic result indicates that： so long as the country established the corresponding rewards and punishments incentive mechanism to the local authority departments responsible for the work, it reports the safety accident in the coal mine on time. The conclusion that the local government displays right and wrong cooperation behavior will be changed with the introduction of the Incomplete Information. Only has the local authority fulfill their responsibility, can the unsafe accident be controlled effectively. Once this kind of cooperation of local government appears, the costs of the country on the safe supervise and the difficulty will be able to decrease greatly.

Comparison Research on Anti-dumping Duty Rates between Administrative Review and Welfare Maximization under Dynamic Game of Perfect Information

Using economics and game theory, two kinds of models have been proposed in this paper under the assumption that foreign and domestic firms behave under the condition of dynamic game of perfect information. One model is for calculating Anti-dumping rate which is obtained according to current regulations of Anti-dumping, but it is not optimal. The other is an optimal model of Anti-dumping which is obtained according to the maximum principle of domestic social welfare. Then, through the comparison of this two models in detail, several shortages have been revealed about Anti-dumping rate model based on current regulations of Anti-dumping. Finally, a suggestion is indicated that WTO and China should use the optimal model to calculate Anti-dumping rate.

Study on the Influence of Winter Olympic Games on Sports Information Work in China

The holding of winter Olympic Games in China indicates that China＇s sports has achieved a great degree of progress. At the same time, it also has a great impact on the sports information work. It will promote a great improvement in sports information access, information services and other aspects, as well as greatly stimulate the progress of sports information work. Therefore, this paper will emphatically analyze the impact on sports information work for holding the winter Olympic Games in China.

Security Defence Policy Selection Method Using the Incomplete Information Game Model

Nowadays, the network defence policy selection using game model of incomplete information ignores the type of the defender, which quantifies cost simply, resulting in unreasonable defence policies selection. Aiming at the problem, we use Bayesian game theory to model the active defence policy selection. We take the types of both the attacker and the defender into consideration. Besides, the traditional quantization method is enhanced. Then, we calculate the equilibrium of static Bayesian game. Based on the analysis of the equilibrium, we select the optimal defence policy through the prediction for attackers' actions. The paper calculates the defence effectiveness of defence policies and provides a defence policies selection algorithm. Ultimately, we present an example to verify the effectiveness of the method and model proposed in the paper.

Threat sequencing of multiple UCAVs with incomplete information based on game theory

The threat sequencing of multiple unmanned combat air vehicles(UCAVs) is a multi-attribute decision-making(MADM)problem. In the threat sequencing process of multiple UCAVs,due to the strong confrontation and high dynamics of the air combat environment, the weight coefficients of the threat indicators are usually time-varying. Moreover, the air combat data is difficult to be obtained accurately. In this study, a threat sequencing method of multiple UCAVs is proposed based on game theory by considering the incomplete information. Firstly, a zero-sum game model of decision maker( D) and nature(N)with fuzzy payoffs is established to obtain the uncertain parameters which are the weight coefficient parameters of the threat indicators and the interval parameters of the threat matrix. Then,the established zero-sum game with fuzzy payoffs is transformed into a zero-sum game with crisp payoffs(matrix game) to solve. Moreover, a decision rule is addressed for the threat sequencing problem of multiple UCAVs based on the obtained uncertain parameters. Finally, numerical simulation results are presented to show the effectiveness of the proposed approach.

Linking a Game Engine Environment to Architectural Information on the Semantic Web

Because of the importance of graphics and information within the domain of architecture, engineering and construction （AEC）, an appropriate combination of visualization technology and information management technology is of utter importance in the development of appropriately supporting design and construction applications. Virtual environments, however, tend not to make this information available. The sparse number of applications that present additional information furthermore tend to limit their scope to pure construction information and do not incorporate information from loosely related knowledge domains, such as cultural heritage or architectural history information. We therefore started an investigation of two of the newest developments in these domains, namely game engine technology and semantic web technology. This paper documents part of this research, containing a review and comparison of the most prominent game engines and documenting our architectural semantic web. A short test-case illustrates how both can be combined to enhance information visualization for architectural design and construction.

Tobacco Agricultural Development in Information Asymmetry——A Case Study of Baise City of Guangxi Province

We adopt sampling method combined with questionnaire to research tobacco agricultural development in Baise City of Guangxi Province. Survey results show that there are problems of inadequate propaganda; guidance and training effort; unreasonable rotation system; backward tobacco baking technologies; low specialized service level; constant increase of costs for means of production and labor employment; low information management level; and frequent occurrence of production accidents. Therefore, it is required to strengthen propaganda and training; enhance technical support; scientifically develop tobacco farmers'cooperative organizations; improve service quality; save labor and reduce cost; improve information management level; reduce institutional operation cost; reinforce guidance of safe production, to promote healthy and orderly development of tobacco agriculture in Guangxi and even in the whole country in the environment of information asymmetry.

Pricing Power of Agricultural Products under the Background of Small Peasant Management and Information Asymmetry

From the background of small peasant management and information asymmetry,this paper introduced the middle profit sharing model and discussed influence factors and ownership of pricing power of agricultural products. It obtained following results:( i) the transaction scale has positive effect on farmer's pricing power of agricultural products,while the competitor's transaction scale has negative effect on it,so does the cost for information search;( ii) under the condition of small peasant management system,farmer is in a relatively weak position in the distribution of pricing power of agricultural products,due to factors such as small transaction scale,information asymmetry and farmer's weak negotiation ability;( iii) through cooperative game,farmer and buyers can share cooperative surplus at the agreed ratio;( iv) the introduction of self-organizing specialized farmers cooperatives is favorable for solving the problem of pricing power of agricultural products,and possible problems,such as " collective action dilemma" and " fake cooperatives" in the cooperative development process can be solved by internal and external division of labor and specialization of cooperatives.

A Study on Estimating the Elements of Card Game Fun Using Biological Information

In this study, we conduct research to estimate the elements of fun in card games. Previously, we tried to estimate the elements of fun by conducting a questionnaire to players, but the results were not good. Therefore, we propose an analysis using the player’s biological information to make a more accurate estimation. Specifically, we try to elucidate the elements of fun by having a player who is playing a game wear a smart watch, and measuring and analyzing the heart rate of that player. This paper conducts an experiment to determine whether our intended data can be collected. As a result, it was found that there is a response to the heart rate in a specific scene, and there is a possibility that the intended data can be collected. We plan to conduct larger experiments in the future.

Dynamic Multi-team Antagonistic Games Model with Incomplete Information and Its Application to Multi-UAV

At present, the studies on multi-team antagonistic games (MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets. Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information (DMTAGII) model. For this model, the corresponding concept of perfect Bayesian Nash equilibrium (PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles (UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm. Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems. © 2014 Chinese Association of Automation.

Sensitive Information Protection Model Based on Bayesian Game

A game measurement model considering the attacker’s knowledge background is proposed based on the Bayesian game theory aiming at striking a balance between the protection of sensitive information and the quality of service.We quantified the sensitive level of information according to the user’s personalized sensitive information protection needs.Based on the probability distribution of sensitive level and attacker’s knowledge background type,the strategy combination of service provider and attacker was analyzed,and a game-based sensitive information protection model was constructed.Through the combination of strategies under Bayesian equilibrium,the information entropy was used to measure the leakage of sensitive information.Furthermore,in the paper the influence of the sensitive level of information and the attacker’s knowledge background on the strategy of both sides of the game was considered comprehensively.Further on,the leakage of the user’s sensitive information was measured.Finally,the feasibility of the model was described by experiments.