A new method to solve intuitionistic fuzzy matrix game based on the evaluation of different experts

In the word of uncertain competitive situations everything is in the state of flux. Under such situations knowing the exact outcomes of mixed strategies adopted by a player is nearly impossible. It is highly rational to assume that no two experts will project the similar fuzzy payoffs for mix of strategies used. Aggregation of expert’s judgement becomes utmost important before solving such competitive situations. Considering this the present paper proposes a method to solve intuitionistic fuzzy game problems by using aggregation operators on payoff judgments of more than one expert. The proposed method significantly adds to the existing literature by overcoming the limitation of Li’s existing method that considers only one expert’s opinion for solving intuitionistic fuzzy game problems. Illustrative example has been given for showing the superiority of the proposed method.

MULTI-AUV DYNAMIC MANEUVER DECISION-MAKING BASED ON INTUITIONISTIC FUZZY COUNTER-GAME AND FRACTIONAL-ORDER PARTICLE SWARM OPTIMIZATION

In this paper, a multi-AUV dynamic maneuver decision-making algorithm is studied based on intuitionistic fuzzy game and fractional-order Particle Swarm Optimization (PSO). Because of the weak communication condition and complex marine environment, a maneuver decision-making algorithm is usually hard to realize in real-time multi-AUV couter-game process. First, the weak communication condition is analyzed according to sonar and other equipment characteristics. Then, the multi-AUV maneuver attributes evaluation and maneuver decision-making modeling are investigated under the obtained weak communication constraints. Subsequently, a fractional-order PSO optimization method is proposed to solve the strategy optimization problem of multi-AUV maneuver decision-making process. At last, an example is presented to verify the effectiveness and superiority of the obtained algorithm.

Choosing a solution based on a fuzzy game with nature

In business process management, semi-structured or unstructured tasks are very common. The predominance of qualitative estimates of the parameters of such problems leads to the fact that the initial requirements for the selection of appropriate information technologies can be formulated primarily at a qualitative level. In this situation, estimates in the form of linguistic statements formalized by fuzzy sets can be quite informative. Uncertainty in the initial data, the presence of several alternative solutions make it possible to formalize the problem of choosing information technology for solving semi-structured business problems as a game with nature, which is understood as a certain combination of conditions, for example, the number of users and the intensity of their requests, assessed by fuzzy, linguistic statements. The aim of the proposed work is to develop a method for finding the most appropriate solution in conditions of indistinctness of the initial data that determine the choice on a variety of possible alternative information technologies. The proposed method for finding the best solution differs in that all the necessary initial estimates are set in the form of linguistic statements formalized by fuzzy sets, while the influence of fuzzy values of the probabilities of states of nature is taken into account through point estimates of fuzzy sets formalizing these values, and an integral estimate of possible solutions is obtained by transformation of the original fuzzy estimates of alternative solutions into the form of equivalent triangular fuzzy sets. In addition, the proposed method makes it possible to use various types of membership functions of fuzzy sets that formalize these estimates when setting fuzzy initial estimates for solving the problem, as well as to simplify the comparison of integral estimates of possible alternative solutions obtained in the form of fuzzy sets.

Growth path of industrial clusters embedded in global value chain from the perspective of knowledge transfer: A fuzzy game approach

How local industrial clusters break through the lock-in status of low end of value chains and realize industrial upgrading in the development process of embedded global value chain is the central topic of current industrial development research. To explore how industrial clusters achieve the enhancement of their innovation capability and value chains when they are embedded in the global value chain, from the perspective of knowledge transfer and according to the differences in the knowledge levels of the local industrial clusters, three fuzzy game models of knowledge transfer paths were constructed, and the model of the realization mechanism of knowledge transfer and its stability condition was analyzed, which make clear the path of cluster growth under different embedding modes. Results show that although the mode of embedding and the path of knowledge transfer is different, the local industrial clusters can obtain external knowledge transfer by embedding in the global value chain; the knowledge transformation ability of local industrial clusters is the determining factor that the knowledge transfer can smoothly achieve and become stable. The conclusion also shows that the feasibility of the cross-sectional growth of industrial clusters by actively embed the global value chain and acquiring external knowledge transfer if the industrial clusters want to enhance their technology accumulation, their innovation ability, and their position in the global value chain.

Artificial intelligent based fuzzy game analysis of migrant students’ studying based on performance and fairness

Artificial Intelligence based Fuzzy Importance Performance Analysis Model (AFIPA)With the transformation of economic system, migrant workers transfer employment from underdeveloped areas to economically developed areas, and children’s reading has become one of the important things for migrant workers and families. With the increase of children in the immigration area year by year, the pressure on education in the immigration area has gradually increased, which has become one of the social problems to be solved by the government in the immigration area. The speed of school construction cannot keep up with the growth of children, and because it takes up a lot of resources, funds and manpower, the government is not very enthusiasticin the immigration area. The stakeholders involved are always playing a game. How to achieve the best state is a difficult problem. After the central government’s policywereissuedabout solving the enrollment problem of migrant workers’children in school, local acceptance criteria for admitting migrant children to school were formulated. However, when lowering the admission threshold, all localities always look to other areas for fear of falling too low to become a basin of confluence, which cause an unbearable burden. In this paper fuzzy based analytic theory has been analysed Through the game analysis of various stakeholders, and taking Shengze Town, Jiangsu Province as an example, this paper puts forward some fuzzy policy suggestions, hoping to provide some new experience in promoting migrant children’s education in the future.

A Methodological Approach to Identifying the Optimal Market Behavior Strategy Based on Fuzzy Game Modeling

The presented study models market behavior strategies for firms in real (“impure”) markets.Aim. The presented study aims to develop tools for optimizing (according to the criterion of profit maximization) the market behavior of firms based on the achievements of modern mathematics.Tasks. The authors describe theoretical approaches to modeling the behavior of firms; define the problem of modeling the market behavior of firms in the language of game theory; modify the game model by implementing elements of the theory of fuzzy logic and fuzzy sets; develop and test a methodological approach to identifying the optimal behavior of firms based on fuzzy game modeling.Methods. This study uses general methods of economic and mathematical modeling, provisions of neoclassical and institutional firm theory, tools of game theory and the theory of fuzzy logic and fuzzy sets.Results. The optimal market behavior strategy for firms selling the same product is determined. The implementation of this strategy focuses on maximizing profits with allowance for the imperfections of real markets. A rigorous solution to this problem is proposed, based on the provisions of game theory, theory of fuzzy sets and fuzzy logic. The developed methodological approach to identifying the optimal market behavior strategy based on fuzzy game modeling is illustrated by a meaningful example.Conclusions. The developed and tested methodological approach to identifying the optimal market behavior strategy based on fuzzy game modeling described in the article allows firms to search for optimal strategies with allowance for the imperfections of real markets. It can be used for theoretical modeling of the behavior of firms in an “impure” market, including in a mixed economy, where the government has a certain degree of planning and administrative influence on economic processes. The proposed approach can be recommended for use by the management of firms in the development and implementation of competitive strategies.

The core and superdifferential of a fuzzy TU-cooperative game

In the paper, we consider conditions providing coincidence of the cores and superdifferentials of fuzzy cooperative games with side payments. It turned out that one of the most simple sufficient conditions consists of weak homogeneity. Moreover, by applying so-called S*-representation of a fuzzy game introduced by the author, we show that for any vwith nonempty core C(v) there exists some game u such that C(v) coincides with the superdifferential of u. By applying subdifferential calculus we describe a structure of the core forboth classic fuzzy extensions of the ordinary cooperative game (e.g., Aubin and Owen extensions) and for some new continuations, like Harsanyi extensions and generalized Airport game.