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1
SÎRGHI, NICOLETA, and MIHAELA NEAMŢU. "DYNAMICS OF DETERMINISTIC AND STOCHASTIC EVOLUTIONARY GAMES WITH MULTIPLE DELAYS." International Journal of Bifurcation and Chaos 23, no. 07 (July 2013): 1350122. http://dx.doi.org/10.1142/s0218127413501228.
Повний текст джерелаАнотація:
In the present paper, we study the effect of time delays in evolutionary games with one population of users and two strategies. The case where the delays, corresponding to different strategies, are not the same is considered. The local stability of the stationary state for the replicator dynamics is analyzed. We show that there is Hopf bifurcation. The stability of the bifurcating periodic solutions is determined by using the center manifold theorem and normal form theory. The stochastic evolutionary game with delay is taken into consideration. We also study the behavior of the first and second solution moments for linear stochastic differential delay equation in the presence of white and colored noise. The last part of the paper includes numerical simulations and conclusions.
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Xu, Xiaotong, Gaocai Wang, Jintian Hu, and Yuting Lu. "Study on Stochastic Differential Game Model in Network Attack and Defense." Security and Communication Networks 2020 (June 8, 2020): 1–15. http://dx.doi.org/10.1155/2020/3417039.
Повний текст джерелаАнотація:
In recent years, evolutionary game theory has been gradually applied to analyze and predict network attack and defense for maintaining cybersecurity. The traditional deterministic game model cannot accurately describe the process of actual network attack and defense due to changing in the set of attack-defense strategies and external factors (such as the operating environment of the system). In this paper, we construct a stochastic evolutionary game model by the stochastic differential equation with Markov property. The evolutionary equilibrium solution of the model is found and the stability of the model is proved according to the knowledge of the stochastic differential equation. And we apply the explicit Euler numerical method to analyze the evolution of the strategy selection of the players for different problem situations. The simulation results show that the stochastic evolutionary game model proposed in this paper can get a steady state and obtain the optimal defense strategy under the action of the stochastic disturbance factor. In addition, compared with other kinds of literature, we can conclude that the return on security investment of this model is better, and the strategy selection of the attackers and defenders in our model is more suitable for actual network attack and defense.
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Song, Yang, Ron Berger, Matti Rachamim, Andrew Johnston, and Andrea Fronzetti Colladon. "Modeling the industry perspective of university-industry collaborative innovation alliances: Player behavior and stability issues." International Journal of Engineering Business Management 14 (January 2022): 184797902210972. http://dx.doi.org/10.1177/18479790221097235.
Повний текст джерелаАнотація:
Many firms find it challenging to develop innovations, evidenced by the ever-mounting number of university-industry research alliances. This study examines the strategic choices of actors who participate in collaborative innovation alliances involving partnerships between industry and universities (U-I) based on a stochastic evolutionary game model. White noise was introduced to reflect uncertainty and the stochastic interferences caused by the differences between actors. Using the Itô stochastic differential equation theory, we analyze stability issues of player behaviors in the evolution of a collaborative innovation alliance. The results illustrate that improvements in innovation efficiency can contribute to U-I collaborative innovation alliances. High knowledge complementarity appears to be unbeneficial to the stability of these alliances, and controlling knowledge spillovers may suppress free-rider problems from both sides of the game. Our study contributes to innovation research by providing a decision-making reference for the design of U-I cooperation.
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Zhu, Qingfeng, Rui Zong, and Mengqi Xu. "Three-Party Stochastic Evolutionary Game Analysis of Supply Chain Finance Based on Blockchain Technology." Sustainability 15, no. 4 (February 8, 2023): 3084. http://dx.doi.org/10.3390/su15043084.
Повний текст джерелаАнотація:
In the process of accounts receivable financing under supply chain finance, the phenomenon of accounts receivable forgery and default have caused great pressure on the supervision of financial institutions. We consider the integration of blockchain technology with a supply chain finance platform around the fraudulent default phenomenon in supply chain finance receivables financing and construct a three-party stochastic evolutionary game model among financial institutions, core enterprises, and Micro, Small, and Medium Enterprises (MSMEs). Firstly, we use Ito^’s stochastic differential equation theory to analyze the conditions for the stability of the behavior of game subjects. Secondly, we use numerical simulations to quantitatively analyze the impact of the regulatory strength of financial institutions, the information sharing of the blockchain platform, and the change of incentive parameters on the strategy choice of game subjects. Through the above analysis, we conclude that the information-sharing incentive coefficient promotes financial institutions to choose to connect to the blockchain platform, and the information-sharing risk coefficient and the regulatory intensity have the opposite effect on the blockchain platform construction. Meanwhile, the allocation of incentive shares has a significant influence on the core enterprises. Finally, we give priorities and directions for adjusting the relevant parameters to provide recommendations for financial institutions to regulate the financing process more effectively.
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Zhou, Da, Bin Wu, and Hao Ge. "Evolutionary stability and quasi-stationary strategy in stochastic evolutionary game dynamics." Journal of Theoretical Biology 264, no. 3 (June 2010): 874–81. http://dx.doi.org/10.1016/j.jtbi.2010.03.018.
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Ohtsuki, Hisashi, and Martin A. Nowak. "Evolutionary games on cycles." Proceedings of the Royal Society B: Biological Sciences 273, no. 1598 (May 23, 2006): 2249–56. http://dx.doi.org/10.1098/rspb.2006.3576.
Повний текст джерелаАнотація:
Traditional evolutionary game theory explores frequency-dependent selection in well-mixed populations without spatial or stochastic effects. But recently there has been much interest in studying the evolutionary game dynamics in spatial settings, on lattices and other graphs. Here, we present an analytic approach for the stochastic evolutionary game dynamics on the simplest possible graph, the cycle. For three different update rules, called ‘birth–death’ (BD), ‘death–birth’ (DB) and ‘imitation’ (IM), we derive exact conditions for natural selection to favour one strategy over another. As specific examples, we consider a coordination game and Prisoner's Dilemma. In the latter case, selection can favour cooperators over defectors for DB and IM updating. We also study the case where the replacement graph of evolutionary updating remains a cycle, but the interaction graph for playing the game is a complete graph. In this setting, all three update rules lead to identical conditions in the limit of weak selection, where we find the ‘1/3-law’ of well-mixed populations.
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Guan, Xin, Guoxing Zhang, Diyi Liu, Xu Tan, and Dong Wu. "The behavior of consumer buying new energy vehicles based on stochastic evolutionary game." Filomat 30, no. 15 (2016): 3987–97. http://dx.doi.org/10.2298/fil1615987g.
Повний текст джерелаАнотація:
China?s current vehicle emissions caused by air pollution problems have become increasingly prominent. How to improve new energy vehicle market share, and effectively guide the consumer buying behavior become a problem, which the government and social have to be solved. In this paper, according to establish the stochastic evolutionary game model between the government and consumers in the car market, introducing of random factors analysis on the impact of evolutionary stability ,will obtain the stable strategy of government and automotive consumers. And on the basis of it, we study the government support, cost of vehicles, the use of cost, the utility of automobile use for the ways of evolutionary stability, with case further illustrates the external disturbance factors on consumer purchase of new energy vehicles in evolutionary game process stability. Studies show that: the increasing government subsidy policy, the reducing life cycle costs of new energy vehicles and the improving effectiveness of new energy vehicles will lead the model?s evolution to the orientation of consumer purchasing new energy vehicles.
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Helbing, Dirk. "A stochastic behavioral model and a ?Microscopic? foundation of evolutionary game theory." Theory and Decision 40, no. 2 (March 1996): 149–79. http://dx.doi.org/10.1007/bf00133171.
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Zhang, Jinxin, and Meng Wu. "Cooperation Mechanism in Blockchain by Evolutionary Game Theory." Complexity 2021 (November 8, 2021): 1–9. http://dx.doi.org/10.1155/2021/1258730.
Повний текст джерелаАнотація:
In the blockchain network, to get rewards in the blockchain, blockchain participants pay for various forms of competition such as computing power, stakes, and other resources. Because of the need to pay a certain cost, individual participants cooperate to maintain the long-term stability of the blockchain jointly. In the course of such competition, the game between each other has appeared invisibly. To better understand the blockchain design of cooperation mechanisms, in this paper, we constructed a game framework between participants with different willingness, using evolutionary game theory, and complex network games. We analyzed how the behavior of participants potentially develops with cost and payoff. We consider the expected benefits of participants for the normal growth of the blockchain as the major factor. Considering the behavior of malicious betrayers, the blockchain needs to be maintained in the early stage. Numerical simulation supports our analysis.
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Brown, Joel S. "Why Darwin would have loved evolutionary game theory." Proceedings of the Royal Society B: Biological Sciences 283, no. 1838 (September 14, 2016): 20160847. http://dx.doi.org/10.1098/rspb.2016.0847.
Повний текст джерелаАнотація:
Humans have marvelled at the fit of form and function, the way organisms' traits seem remarkably suited to their lifestyles and ecologies. While natural selection provides the scientific basis for the fit of form and function, Darwin found certain adaptations vexing or particularly intriguing: sex ratios, sexual selection and altruism. The logic behind these adaptations resides in frequency-dependent selection where the value of a given heritable phenotype (i.e. strategy) to an individual depends upon the strategies of others. Game theory is a branch of mathematics that is uniquely suited to solving such puzzles. While game theoretic thinking enters into Darwin's arguments and those of evolutionists through much of the twentieth century, the tools of evolutionary game theory were not available to Darwin or most evolutionists until the 1970s, and its full scope has only unfolded in the last three decades. As a consequence, game theory is applied and appreciated rather spottily. Game theory not only applies to matrix games and social games, it also applies to speciation, macroevolution and perhaps even to cancer. I assert that life and natural selection are a game, and that game theory is the appropriate logic for framing and understanding adaptations. Its scope can include behaviours within species, state-dependent strategies (such as male, female and so much more), speciation and coevolution, and expands beyond microevolution to macroevolution. Game theory clarifies aspects of ecological and evolutionary stability in ways useful to understanding eco-evolutionary dynamics, niche construction and ecosystem engineering. In short, I would like to think that Darwin would have found game theory uniquely useful for his theory of natural selection. Let us see why this is so.
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Nowak, Martin A., Corina E. Tarnita, and Tibor Antal. "Evolutionary dynamics in structured populations." Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1537 (January 12, 2010): 19–30. http://dx.doi.org/10.1098/rstb.2009.0215.
Повний текст джерелаАнотація:
Evolutionary dynamics shape the living world around us. At the centre of every evolutionary process is a population of reproducing individuals. The structure of that population affects evolutionary dynamics. The individuals can be molecules, cells, viruses, multicellular organisms or humans. Whenever the fitness of individuals depends on the relative abundance of phenotypes in the population, we are in the realm of evolutionary game theory. Evolutionary game theory is a general approach that can describe the competition of species in an ecosystem, the interaction between hosts and parasites, between viruses and cells, and also the spread of ideas and behaviours in the human population. In this perspective, we review the recent advances in evolutionary game dynamics with a particular emphasis on stochastic approaches in finite sized and structured populations. We give simple, fundamental laws that determine how natural selection chooses between competing strategies. We study the well-mixed population, evolutionary graph theory, games in phenotype space and evolutionary set theory. We apply these results to the evolution of cooperation. The mechanism that leads to the evolution of cooperation in these settings could be called ‘spatial selection’: cooperators prevail against defectors by clustering in physical or other spaces.
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Lu, Yu Mei. "Evolutionary Game Theory-Based Modeling and Stability Analysis of Subsidy Policy on Safety Investment in SMEs." Applied Mechanics and Materials 39 (November 2010): 575–79. http://dx.doi.org/10.4028/www.scientific.net/amm.39.575.
Повний текст джерелаАнотація:
Evolutionary game theory originated as an application of the mathematical theory of games to biological contexts, having the advantages of truly reflecting the diversity and complexity to provide theoretical basis to study macro-control group behavior. The evolutionary game theory-based modeling and stability analysis of subsidy policy on safety investment in SMEs is studied, and the simulation about the effect of the alteration of the ratio on the evolvement results is executed. The results indicate that the safety subsidy of local governments can enhance SMEs’ enthusiasm to invest. It has excellent significance to study further how to achieve equilibrium between SMEs and local governments using evolutionary game theory, and to provide theoretical basis to study operation mode of subsidy policy on safety investment in SMEs.
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Xu, Yan, Benhai Yu, Youtian Wang, and Yanliang Chen. "A stochastic evolutionary game perspective on the stability of strategic alliances against external opportunism." Journal of Systems Science and Complexity 28, no. 4 (January 22, 2015): 978–96. http://dx.doi.org/10.1007/s11424-015-2104-x.
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Tao, Yi, and Ross Cressman. "Stochastic Fluctuations Through Intrinsic Noise in Evolutionary Game Dynamics." Bulletin of Mathematical Biology 69, no. 4 (February 21, 2007): 1377–99. http://dx.doi.org/10.1007/s11538-006-9170-0.
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Zhu, Qingfeng, Kaimin Zheng, and Yilin Wei. "Three-Party Stochastic Evolutionary Game Analysis of Reward and Punishment Mechanism for Green Credit." Discrete Dynamics in Nature and Society 2021 (June 16, 2021): 1–12. http://dx.doi.org/10.1155/2021/5596015.
Повний текст джерелаАнотація:
To get rid of the development dilemma of green credit, we constructed a stochastic evolutionary game model of local government, commercial banks, and loan enterprises. We gave sufficient conditions for the stability of strategy based on the stability discriminant theorem of It o ^ ' s stochastic differential equation (SDE). Then, we discussed the impacts of incentive and penalty parameters on green credit. Through the above analysis, we got the following conclusions: (1) rewards and punishments always benefit green production and green credit, but increasing incentives is not conducive to the governments’ performance of regulatory duties; (2) punishments can better improve the convergence rate of players’ strategy than rewards; and (3) both rewards and punishments can exert an obvious effect in improving the changing degree of players’ strategy. Finally, we put forward some suggestions to optimize the green credit mechanism.
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Zhao, Yuntong, and Yushen Du. "Technical standard competition: An ecosystem-view analysis based on stochastic evolutionary game theory." Technology in Society 67 (November 2021): 101794. http://dx.doi.org/10.1016/j.techsoc.2021.101794.
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Dua, Rajvir, Yongqian Ma, and Paul K. Newton. "Are Adaptive Chemotherapy Schedules Robust? A Three-Strategy Stochastic Evolutionary Game Theory Model." Cancers 13, no. 12 (June 9, 2021): 2880. http://dx.doi.org/10.3390/cancers13122880.
Повний текст джерелаАнотація:
We investigate the robustness of adaptive chemotherapy schedules over repeated cycles and a wide range of tumor sizes. Using a non-stationary stochastic three-component fitness-dependent Moran process model (to track frequencies), we quantify the variance of the response to treatment associated with multidrug adaptive schedules that are designed to mitigate chemotherapeutic resistance in an idealized (well-mixed) setting. The finite cell (N tumor cells) stochastic process consists of populations of chemosensitive cells, chemoresistant cells to drug 1, and chemoresistant cells to drug 2, and the drug interactions can be synergistic, additive, or antagonistic. Tumor growth rates in this model are proportional to the average fitness of the tumor as measured by the three populations of cancer cells compared to a background microenvironment average value. An adaptive chemoschedule is determined by using the N→∞ limit of the finite-cell process (i.e., the adjusted replicator equations) which is constructed by finding closed treatment response loops (which we call evolutionary cycles) in the three component phase-space. The schedules that give rise to these cycles are designed to manage chemoresistance by avoiding competitive release of the resistant cell populations. To address the question of how these cycles perform in practice over large patient populations with tumors across a range of sizes, we consider the variances associated with the approximate stochastic cycles for finite N, repeating the idealized adaptive schedule over multiple periods. For finite cell populations, the distributions remain approximately multi-Gaussian in the principal component coordinates through the first three cycles, with variances increasing exponentially with each cycle. As the number of cycles increases, the multi-Gaussian nature of the distribution breaks down due to the fact that one of the three sub-populations typically saturates the tumor (competitive release) resulting in treatment failure. This suggests that to design an effective and repeatable adaptive chemoschedule in practice will require a highly accurate tumor model and accurate measurements of the sub-population frequencies or the errors will quickly (exponentially) degrade its effectiveness, particularly when the drug interactions are synergistic. Possible ways to extend the efficacy of the stochastic cycles in light of the computational simulations are discussed.
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Li, Junqiang, Jingyi Yi, and Yingmei Zhao. "Effective Boundary of Innovation Subsidy: Searching by Stochastic Evolutionary Game Model." Symmetry 12, no. 9 (September 16, 2020): 1531. http://dx.doi.org/10.3390/sym12091531.
Повний текст джерелаАнотація:
Relationship between innovation subsidies and corporate strategic choices has been extensively studied. Public innovation subsidies are by no means a certain value, existing in the form of an effective range instead. This means that the public innovation subsidies existing within the reasonable range can achieve the same incentive effect. So, what is the reasonable range or the effective boundaries of public innovation subsidies to promote enterprises that adopt cooperation strategies? There is no definite answer. Based on classical game theory, a stochastic evolutionary game model is proposed in this paper, which takes into account the influence of random disturbance on the strategy evolution process. An effective boundary of public innovation subsidy is provided as the main contribution based on a mature game scenario. A set of experimental data is subsequently selected as the sample for numerical simulation and result verification. The results showed that the probability of noncooperation within the effective value range will successfully converge to zero, which also means that the agents will adopt a collaborative cooperation strategy. The regulation effect of the combination of multiple variables is also discussed.
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Araujo, Ricardo Azevedo, and Helmar Nunes Moreira. "Lyapunov stability in an evolutionary game theory model of the labour market." EconomiA 15, no. 1 (January 2014): 41–53. http://dx.doi.org/10.1016/j.econ.2014.03.006.
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Venkateswaran, Vandana Revathi, and Chaitanya S. Gokhale. "Evolutionary dynamics of complex multiple games." Proceedings of the Royal Society B: Biological Sciences 286, no. 1905 (June 26, 2019): 20190900. http://dx.doi.org/10.1098/rspb.2019.0900.
Повний текст джерелаАнотація:
Evolutionary game theory has been successful in describing phenomena from bacterial population dynamics to the evolution of social behaviour. However, it has typically focused on a single game describing the interactions between individuals. Organisms are simultaneously involved in many intraspecies and interspecies interactions. Therefore, there is a need to move from single games to multiple games. However, these interactions in nature involve many players. Shifting from 2-player games to multiple multiplayer games yield richer dynamics closer to natural settings. Such a complete picture of multiple game dynamics (MGD), where multiple players are involved, was lacking. For multiple multiplayer games—where each game could have an arbitrary finite number of players and strategies, we provide a replicator equation for MGD having many players and strategies. We show that if the individual games involved have more than two strategies, then the combined dynamics cannot be understood by looking only at individual games. Expected dynamics from single games is no longer valid, and trajectories can possess different limiting behaviour. In the case of finite populations, we formulate and calculate an essential and useful stochastic property, fixation probability. Our results highlight that studying a set of interactions defined by a single game can be misleading if we do not take the broader setting of the interactions into account. Through our results and analysis, we thus discuss and advocate the development of evolutionary game(s) theory, which will help us disentangle the complexity of multiple interactions.
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SANTAMARIA-GARCIA, JUANA. "BARGAINING POWER IN THE NASH DEMAND GAME AN EVOLUTIONARY APPROACH." International Game Theory Review 11, no. 01 (March 2009): 87–97. http://dx.doi.org/10.1142/s0219198909002200.
Повний текст джерелаАнотація:
A population of buyers and a population of sellers meet repeatedly in order to exchange a good. The price is fixed through a variant of the Nash demand game. This paper analyzes the prices that are robust to experimentation in the sense of stochastic stability. Under some conditions only one price is selected and it gives a share of the surplus to each side of the market that corresponds to the generalized Nash bargaining solution. The bargaining power of each party depends on the division of the unclaimed surplus and the population sizes. The bargaining power of a given population will increase either with a reduction in its fraction of the unclaimed surplus or with a decrease in its own size.
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Li, Dan. "Research on Organization Tacit Knowledge Transferring: An Evolutionary Game Theoretic Analysis." Advanced Materials Research 756-759 (September 2013): 2597–601. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2597.
Повний текст джерелаАнотація:
The transfer and the management of the tacit knowledge is one of the most important issues in the knowledge transferring context to create organizational competitive advantage in the fast growing competitive world. As we know, organization tacit knowledge transferring is a dynamic game process, this research applies evolutionary game theory to analyze the tacit knowledge transferring activities among organizations and the stability balance issue in organization knowledge transferring. Based on the theory of games, this paper constructs the evolutionary game process model for organization tacit knowledge transferring. And through the equilibrium point of the model, the different knowledge transferring bodies game replicated dynamics and stability are analyzed. With this model, the reason why tacit knowledge is hard to be transferred and the path of tacit knowledge transferring is analyzed.
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Parke, William R., and George A. Waters. "ON THE EVOLUTIONARY STABILITY OF RATIONAL EXPECTATIONS." Macroeconomic Dynamics 18, no. 7 (June 18, 2013): 1581–606. http://dx.doi.org/10.1017/s1365100513000059.
Повний текст джерелаАнотація:
Evolutionary game theory provides a fresh perspective on the prospect that agents with heterogeneous expectations might eventually come to agree on a single expectation corresponding to the efficient markets hypothesis. We establish conditions under which agreement on a unique forecast is stable, but also show that persistent heterogeneous expectations can arise if those conditions do not hold. The critical element is the degree of curvature in the payoff weighting functions agents use to value forecasting performance. We illustrate our results in the context of an asset pricing model where a martingale solution competes with the fundamental solution for agents' attention.
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Yang, Yujing, Junhai Ma, and Hongliang Tu. "Chaotic Characteristics and Application of Cooperative Game and Evolutionary Game." Discrete Dynamics in Nature and Society 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/908093.
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According to a dynamical multiteam Cournot game in exploitation of a renewable resource, a new dynamic Cournot duopoly game model with team players in exploitation of a renewable resource is built up in this paper. Based on the theory of bifurcations of dynamical systems, the stability of the system is studied and the local stable region of Nash equilibrium point is obtained. The effect of the output adjustment speed parameters and the weight parameter of the system on the dynamic characteristics of the system are researched. The complexity of the system is described via the bifurcation diagrams, the Lyapunov exponents, the phase portrait, the time history diagram, and the fractal dimension. Furthermore, the chaos control of the system is realized by the parameter adjustment method. At last, an evolutionary game as a special dynamic system is constructed and analyzed which is more useful and helpful in application. The derived results have very important theoretical and practical values for the renewable resource market and companies.
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Gatti, Nicola, Fabio Panozzo, and Marcello Restelli. "Efficient Evolutionary Dynamics with Extensive-Form Games." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (June 30, 2013): 335–41. http://dx.doi.org/10.1609/aaai.v27i1.8600.
Повний текст джерелаАнотація:
Evolutionary game theory combines game theory and dynamical systems and is customarily adopted to describe evolutionary dynamics in multi-agent systems. In particular, it has been proven to be a successful tool to describe multi-agent learning dynamics. To the best of our knowledge, we provide in this paper the first replicator dynamics applicable to the sequence form of an extensive-form game, allowing an exponential reduction of time and space w.r.t. the currently adopted replicator dynamics for normal form. Furthermore, our replicator dynamics is realization equivalent to the standard replicator dynamics for normal form. We prove our results for both discrete-time and continuous-time cases. Finally, we extend standard tools to study the stability of a strategy profile to our replicator dynamics.
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Ruelas, Rocio E., David G. Rand, and Richard H. Rand. "Nonlinear parametric excitation of an evolutionary dynamical system." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 226, no. 8 (December 14, 2011): 1912–20. http://dx.doi.org/10.1177/0954406211432066.
Повний текст джерелаАнотація:
Nonlinear parametric excitation refers to the nonlinear analysis of a system of ordinary differential equations with periodic coefficients. In contrast to linear parametric excitation, which offers determinations of the stability of equilibria, nonlinear parametric excitation has as its goal the structure of the phase space, as given by a portrait of the Poincare map. In this article, perturbation methods and numerical integration are applied to the replicator equation with periodic coefficients, being a model from evolutionary game theory where evolutionary dynamics are added to classical game theory using differential equations. In particular, we study evolution in the Rock–Paper–Scissors game, which has biological and social applications. Here, periodic coefficients could represent seasonal variation.
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Marsan, G. Ajmone, N. Bellomo, and L. Gibelli. "Stochastic evolutionary differential games toward a systems theory of behavioral social dynamics." Mathematical Models and Methods in Applied Sciences 26, no. 06 (April 12, 2016): 1051–93. http://dx.doi.org/10.1142/s0218202516500251.
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This paper proposes a systems approach to social sciences based on a mathematical framework derived from a generalization of the mathematical kinetic theory and of theoretical tools of game theory. Social systems are modeled as a living evolutionary ensemble composed of many individuals, who express specific strategies, cooperate, compete and might aggregate into groups which pursue a common interest. A critical analysis on the complexity features of social system is developed and a differential structure is derived to provide a general framework toward modeling. Then, a case study shows how the systems approach is applied. Moreover, it is shown how the theory leads to the interpretation and use of the so-called big data. Finally some research perspectives are brought to the attention of readers.
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Gu, Qianqian, Lei Hang, and Shaorong Sun. "Behavioral Game Theory Model in Pollution Control with Additional Supervision." Algorithms 15, no. 5 (April 21, 2022): 137. http://dx.doi.org/10.3390/a15050137.
Повний текст джерелаАнотація:
The work is devoted to the study of the impact of external control on the strategies of pollutant discharge enterprises and government regulators in the field of environmental protection. The authors construct a model of the relationship between these entities. It is an evolutionary game in which the players are entities that generate pollutants and the government departments that implement pollution supervision. The choice of strategies of both of these entities and the evolutionary stability of the system controlled by different regulatory efforts, i.e., a third party, are analyzed. The authors then verify the evolutionary paths and evolutionary results of the model under different conditions using simulation analysis based on this model. The conducted research shows that the weak power of third-party supervision is not enough to promote the evolution of the behavioral decisions of the government and enterprises. An appropriate increase in the power of third-party supervision will change the choice of the government and enterprises strategies in the short term; however, due to the mutual influence of the strategies between both sides of the game, in this situation, the evolutionary system does not pursue a stable state. The strong power of third-party supervision will push enterprises to choose a pollution control strategy, change the intensity of government supervision, and replace government supervision to a certain extent. It is an interesting example of modeling the relationship of this system on the basis of evolutionary game theory. The findings can be regarded as a theoretical reference for environmental pollution control of enterprises.
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Zhang, Guoxing, Zhenhua Zhang, Yongjing Cui, and Chun Yuan. "Game model of enterprises and government based on the tax preference policy for energy conservation and emission reduction." Filomat 30, no. 15 (2016): 3963–74. http://dx.doi.org/10.2298/fil1615963z.
Повний текст джерелаАнотація:
In recent years, greater efforts in tax preference policy for energy conservation and emission reduction (ECER) have been implemented in our country. Based on the tax preference of enterprise income for comprehensive utilization of resources, the constraints to achieve completely successful equilibrium are studied in the single period and multiple periods. In the single period, the key to achieve separating equilibrium is analyzed carefully by constructing a signaling game model of enterprises and government on tax preference of enterprise income. In the multiple periods, with the stochastic evolutionary game model based on the stochastic differential equation (SDE) theory, the constraints of keeping the separating equilibrium stable and continuing in a long term will be further investigated. It gives the optimal number of tax preference of enterprise income, camouflage cost and expected cost of risk under the state of separating equilibrium. The optimal result of completely successful equilibrium is obtained in single period by the analysis of numerical example for enterprises and government signaling game model. The simulation experiment is successfully finished to test the effectiveness of the stochastic evolutionary game model by using mathematical software MATLAB.
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Zhang, Yuchen, and Jing Liu. "Optimal Decision-Making Approach for Cyber Security Defense Using Game Theory and Intelligent Learning." Security and Communication Networks 2019 (December 23, 2019): 1–16. http://dx.doi.org/10.1155/2019/3038586.
Повний текст джерелаАнотація:
Existing approaches of cyber attack-defense analysis based on stochastic game adopts the assumption of complete rationality, but in the actual cyber attack-defense, it is difficult for both sides of attacker and defender to meet the high requirement of complete rationality. For this aim, the influence of bounded rationality on attack-defense stochastic game is analyzed. We construct a stochastic game model. Aiming at the problem of state explosion when the number of network nodes increases, we design the attack-defense graph to compress the state space and extract network states and defense strategies. On this basis, the intelligent learning algorithm WoLF-PHC is introduced to carry out strategy learning and improvement. Then, the defense decision-making algorithm with online learning ability is designed, which helps to select the optimal defense strategy with the maximum payoff from the candidate strategy set. The obtained strategy is superior to previous evolutionary equilibrium strategy because it does not rely on prior data. By introducing eligibility trace to improve WoLF-PHC, the learning speed is further improved and the defense timeliness is significantly promoted.
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Guo, Shengyu, Pan Zhang, and Jianying Yang. "SYSTEM DYNAMICS MODEL BASED ON EVOLUTIONARY GAME THEORY FOR QUALITY SUPERVISION AMONG CONSTRUCTION STAKEHOLDERS." Journal of Civil Engineering and Management 24, no. 4 (June 29, 2018): 318–30. http://dx.doi.org/10.3846/jcem.2018.3068.
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To address the gap, that is, few studies have explored the influence of the participants’ interactions with one another during construction quality supervision, this paper proposes a system dynamics model based on evolutionary game theory to describe the complex and dynamic interactions among tripartite stakeholders in China, including the project owner (PO), construction supervising engineer (CSE), and construction contractor (CC). First, the replicated dynamic equation set is established in terms of expense targets. Second, the equilibrium solutions of the equation set are obtained to test strategy options. The trends of system fluctuations caused by penalty and reward changes are also analyzed. Finally, the stability of the proposed model is improved by integrating a dynamic penalty–reward scenario into the evolutionary strategy of the PO. Simulation results show that: 1) the evolutionary stable strategy does not exist in initial interactions, 2) the degrees of penalty and reward considerably affect the CC’s rate variable, and 3) the dynamic penalty–reward scenario could effectively improve the stability of the proposed model. The unsteadiness of the quality supervision system and the stability control scenario could help in understanding the impact of interactions among stakeholders and provide suggestions for optimizing quality supervision procedures.
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Yuan, Huiqun, Ya Bi, Han-Chi Fu, and Anthony Lam. "Stability analysis of supply chain in evolutionary game based on stability theory of nonlinear differential equation." Alexandria Engineering Journal 59, no. 4 (August 2020): 2331–37. http://dx.doi.org/10.1016/j.aej.2020.02.025.
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BORKAR, V. S. "REINFORCEMENT LEARNING IN MARKOVIAN EVOLUTIONARY GAMES." Advances in Complex Systems 05, no. 01 (March 2002): 55–72. http://dx.doi.org/10.1142/s0219525902000535.
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A population of agents plays a stochastic dynamic game wherein there is an underlying state process with a Markovian dynamics that also affects their costs. A learning mechanism is proposed which takes into account intertemporal effects and incorporates an explicit process of expectation formation. The agents use this scheme to update their mixed strategies incrementally. The asymptotic behavior of this scheme is captured by an associated ordinary differential equation. Both the formulation and the analysis of the scheme draw upon the theory of reinforcement learning in artificial intelligence.
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Shi, Leyi, Xiran Wang, and Huiwen Hou. "Research on Optimization of Array Honeypot Defense Strategies Based on Evolutionary Game Theory." Mathematics 9, no. 8 (April 8, 2021): 805. http://dx.doi.org/10.3390/math9080805.
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Honeypot has been regarded as an active defense technology that can deceive attackers by simulating real systems. However, honeypot is actually a static network trap with fixed disposition, which is easily identified by anti-honeypot technology. Thus, honeypot is a “passive” active defense technology. Dynamic honeypot makes up for the shortcomings of honeypot, which dynamically adjusts defense strategies with the attack of hackers. Therefore, the confrontation between defenders and attackers is a strategic game. This paper focuses on the non-cooperative evolutionary game mechanism of bounded rationality, aiming to improve the security of the array honeypot system through the evolutionarily stable strategies derived from the evolutionary game model. First, we construct a three-party evolutionary game model of array honeypot, which is composed of defenders, attackers and legitimate users. Secondly, we formally describe the strategies and revenues of players in the game, and build the three-party game payoff matrices. Then the evolutionarily stable strategy is obtained by analyzing the Replicator Dynamics of various parties. In addition, we discuss the equilibrium condition to get the influence of the number of servers N on the stability of strategy evolution. MATLAB and Gambit simulation experiment results show that deduced evolutionarily stable strategies are valid in resisting attackers.
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Zhao, Daozhi, Jiaqin Hao, Cejun Cao, and Hongshuai Han. "Evolutionary Game Analysis of Three-Player for Low-Carbon Production Capacity Sharing." Sustainability 11, no. 11 (May 28, 2019): 2996. http://dx.doi.org/10.3390/su11112996.
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In the era of the sharing economy, the rise of production capacity sharing has changed traditional manufacturing modes and broken the balance of original production systems. In addition to that environmental-friendly manufacturing enterprises are of great significance with regard to production capacity sharing and sustainable development of the ecology environment. To investigate the decision-making behaviors of the participants involved in low-carbon production capacity sharing, an evolutionary game model taking into account the platforms, manufacturing enterprises with idle production capacity, and those with demanding production capacity is constructed. Then, both evolutionary game theory and Lyapunov stability theorem are used to analyze the asymptotic stability of the equilibrium and evolutionary stability strategies of the system. Besides, the economic and managerial significance of the evolutionary stability strategy is given. Finally, the influence of low-carbon production capacity of enterprises on the stability of the dynamic system is discussed, such as the cost effect of low-carbon production capacity, the effect of transaction cost, and so on. Results indicate that they can provide theoretical reference for decision-making with respect to the platforms, manufacturing enterprises, and sustainable development of the dynamic system.
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Wu, Zenan, Liqin Tian, Yi Zhang, Yan Wang, and Yuquan Du. "Network Attack and Defense Modeling and System Security Analysis: A Novel Approach Using Stochastic Evolutionary Game Petri Net." Security and Communication Networks 2021 (November 13, 2021): 1–10. http://dx.doi.org/10.1155/2021/4005877.
Повний текст джерелаАнотація:
At present, most network security analysis theory assumes that the players are completely rational. However, this is not consistent with the actual situation. In this paper, based on the effectiveness constraints on both sides with network attack and defense, with the help of stochastic Petri net and evolutionary game theory, the Petri net model of network attack and defense stochastic evolutionary game is reconstructed, the specific definition of the model is given, and the modeling method is given through the network connection relationship and attack and defense strategy set. Using this model, a quantitative analysis of network attack events is carried out to solve a series of indicators related to system security, namely, attack success rate, average attack time, and average system repair time. Finally, the proposed model and analysis method are applied to a classic network attack and defense process for experimental analysis, and the results verify the rationality and accuracy of the model and analysis method.
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Qu, Guohua, Yanfang Wang, Ling Xu, Weihua Qu, Qiang Zhang, and Zeshui Xu. "Low-Carbon Supply Chain Emission Reduction Strategy Considering the Supervision of Downstream Enterprises Based on Evolutionary Game Theory." Sustainability 13, no. 5 (March 5, 2021): 2827. http://dx.doi.org/10.3390/su13052827.
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In order to explore the issue of multi-party collaborative governance of energy conservation and emission reduction under the perspective of the low-carbon supply chain, the participation of downstream enterprises as an effective source of local government supervision is included in the selection of low-carbon behaviors of suppliers. First, this paper establishes a tripartite evolutionary game model among local governments, suppliers and downstream enterprise groups. By calculating and copying dynamic equations, the asymptotic stability analysis of the three parties of the game is performed and the stability of the Jacobian matrix proposed by Friedman is used to analyze the local stability of the model equilibrium point and the evolutionary stability strategy of the system. Secondly, the evolution results and evolution paths of the model under different strategies are simulated by system dynamics and the influence of different parameters on the main body selection strategy of the tripartite game is analyzed. Finally, the paper puts forward corresponding policy suggestions from the perspectives of local government, suppliers and downstream enterprises in order to provide new ideas for the governance of China’s environmental problems from the perspective of low carbon.
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Zhao, Danyu, Li Song, and Liangliang Han. "Evolutionary Game Analysis of Debt Restructuring Involved by Asset Management Companies." Complexity 2022 (April 18, 2022): 1–18. http://dx.doi.org/10.1155/2022/2651538.
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Based on the evolutionary game theory, this article constructs a quartet evolutionary game model for debt restructuring with the participation of asset management companies; studies the interactive mechanism of complex behaviors among the government, banks, asset management companies, and enterprises; and analyzes the stability of the strategies of each game subject. It also analyzes the stability of the equilibrium points in the system and finds the stable points that maximize the interests of each subject. Research shows that the government chooses to give specific support, banks choose debt-to-equity swaps, asset management companies choose to provide liquidity, and enterprises choose to work hard, which can better promote the debt restructuring process. Finally, using Matlab2018 software to analyze the impact of each essential element in the debt restructuring on the stability of system evolution, the research results provide a basis for the successful debt restructuring of the enterprises.
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Hilbe, Christian. "Local Replicator Dynamics: A Simple Link Between Deterministic and Stochastic Models of Evolutionary Game Theory." Bulletin of Mathematical Biology 73, no. 9 (December 23, 2010): 2068–87. http://dx.doi.org/10.1007/s11538-010-9608-2.
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Lyu, Ledi, Zeguang Cui, and Haomin Zhang. "Game modelling and stability strategy research on distributed leadership pattern: A tripartite evolutionary game perspective." PLOS ONE 17, no. 7 (July 20, 2022): e0271721. http://dx.doi.org/10.1371/journal.pone.0271721.
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Distributed leadership pattern has been a topic of growing interest in recent years, recognizing that much remains to be known about this phenomenon. The research on distributed leadership acknowledges that responsibility and power are not exclusively limited to one formal leader, but are distributed between formal and informal leaders. The decision-making behavior of team members plays a vital role in optimizing cooperation and team performance. Nevertheless, little attention is paid to investigating the underlying mechanisms about how people in a team cooperate to initiate effective interactions and enhance team performance. Game theory offers a comprehensive analysis of rational behavior under the circumstances of strategic interdependence. By organizing the formal leader, the informal leader, and the ordinary employee in a team, this study constructs a tripartite evolutionary game model and analyzes the internal mechanism of distributed leadership patterns. The study finds that the equilibrium of the three parties is affected by multiple factors. The simulation results reveal that the empowerment of the formal leader to the informal leader is indispensable to promoting optimal cooperation and team performance in distributed leadership patterns. These findings have theoretical implications for the distributed leadership literature and managerial implications for practitioners.
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Yu, Kai, Lujie Zhou, Qinggui Cao, and Zhen Li. "Evolutionary Game Research on Symmetry of Workers’ Behavior in Coal Mine Enterprises." Symmetry 11, no. 2 (January 31, 2019): 156. http://dx.doi.org/10.3390/sym11020156.
Повний текст джерелаАнотація:
Statistics show that humans’ unsafe behaviors are the main cause of accidents. Because of the asymmetry of game benefits between managers and coal miners, the stability of workers’ behaviors is affected and unsafe behaviors are produced. In this paper, the symmetry of the behavior benefits of coal mine workers is studied, using game theory. In order to observe the dynamic game evolution process of behavioral stability, the paper establishes a system dynamics (SD) model and simulates it. The SD simulation results show that with the continuation of the game, when the benefits for safety managers and workers are asymmetric and the safety manager’s safety inspection benefits are less than the non-inspection benefits, the manager may not conduct safety inspections, which poses a great hidden danger to safety production. Through dynamic incentives to regulate the symmetry of income of coal mine safety managers and coal mine workers, the purpose of enhancing the stability of safety behavior is achieved. The research results of the paper have been successfully applied to coal mine enterprises.
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Duan, Xuan, Pengfei Sun, Xu Wang, and Bisheng Zhan. "Evolutionary Game Analysis of Industry-University-Research Cooperative Innovation in Digital Media Enterprise Cluster Based on GS Algorithm." Wireless Communications and Mobile Computing 2022 (August 16, 2022): 1–10. http://dx.doi.org/10.1155/2022/5701917.
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In order to study all the advantages and disadvantages of digital media enterprises, technological innovation can only be completed through cooperation. A kind of industry-university-research cooperative innovation evolutionary game method based on GS algorithm is proposed for digital media enterprise clusters. This method analyzes the evolutionary game theory of innovation and puts forward the evolutionary stability strategy of cooperative innovation between enterprises and research institutions. The results show that decreasing V is beneficial for the evolutionary game to approach the equilibrium point (1,1); that is, the greater the cost of independent innovation is compared with collaborative innovation, the stronger the willingness of both sides of the game to collaborative innovation. Enterprises and scientific research institutions are two different subjects with different interests. If they want to complete innovation cooperation, they need to formulate a perfect set of rules so that both sides of the game can carry out cooperative innovation according to the principles, so as to achieve the goal of cooperation.
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Matsuda, Yusuke, Masahiro Sasabe, and Tetsuya Takine. "Evolutionary Game Theory-Based Evaluation of P2P File-Sharing Systems in Heterogeneous Environments." International Journal of Digital Multimedia Broadcasting 2010 (2010): 1–12. http://dx.doi.org/10.1155/2010/369814.
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Peer-to-Peer (P2P) file sharing is one of key technologies for achieving attractive P2P multimedia social networking. In P2P file-sharing systems, file availability is improved by cooperative users who cache and share files. Note that file caching carries costs such as storage consumption and processing load. In addition, users have different degrees of cooperativity in file caching and they are in different surrounding environments arising from the topological structure of P2P networks. With evolutionary game theory, this paper evaluates the performance of P2P file sharing systems in such heterogeneous environments. Using micro-macro dynamics, we analyze the impact of the heterogeneity of user selfishness on the file availability and system stability. Further, through simulation experiments with agent-based dynamics, we reveal how other aspects, for example, synchronization among nodes and topological structure, affect the system performance. Both analytical and simulation results show that the environmental heterogeneity contributes to the file availability and system stability.
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Su, Xin, Haolong Liu, and Shunqi Hou. "The Trilateral Evolutionary Game of Agri-Food Quality in Farmer-Supermarket Direct Purchase: A Simulation Approach." Complexity 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/5185497.
Повний текст джерелаАнотація:
The prevalence of opportunistic behaviors in agri-food production and circulation results in frequent quality accidents in emerging economies. Numerous researches have discussed effective countermeasures to this problem, but few of them focus on the effectiveness and stability of quality assurance systems. Owing to the bounded rationality and information asymmetry, the dynamic quality game among producers, marketers, and consumers has significant characteristics of complexity. This paper aims at discussing the farmer-supermarket direct purchase’s contributions to ensure the agri-food quality and analyzing the effectiveness, stability, and key factors of this new industrial organization. Based on the evolutionary game theory, we establish the trilateral-game payoff matrix, build up the replicator dynamic equations, and discuss possible evolutionary stable states. The simulation results show that the evolutionary system converges to desired stability faster, when the high-quality agri-food’s market premium increases and the penalty for violating quality standards increases. Furthermore, when farmers share more high-quality agri-food’s market premiums and marketers compensate more for violating the quality standards than before, the evolutionary system also converges to desired stability faster. Therefore, the quality information tracing technology, farmers and marketers’ fair distribution of profits and risks, and consumers’ capabilities to safeguard their legal rights are the three key factors to maintain the effectiveness and stability of quality assurance systems.
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Shao, Zihao, Huiqiang Wang, and Guangsheng Feng. "PUEGM: A Method of User Revenue Selection Based on a Publisher-User Evolutionary Game Model for Mobile Crowdsensing." Sensors 19, no. 13 (July 2, 2019): 2927. http://dx.doi.org/10.3390/s19132927.
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Mobile crowdsensing (MCS) is a way to use social resources to solve high-precision environmental awareness problems in real time. Publishers hope to collect as much sensed data as possible at a relatively low cost, while users want to earn more revenue at a low cost. Low-quality data will reduce the efficiency of MCS and lead to a loss of revenue. However, existing work lacks research on the selection of user revenue under the premise of ensuring data quality. In this paper, we propose a Publisher-User Evolutionary Game Model (PUEGM) and a revenue selection method to solve the evolutionary stable equilibrium problem based on non-cooperative evolutionary game theory. Firstly, the choice of user revenue is modeled as a Publisher-User Evolutionary Game Model. Secondly, based on the error-elimination decision theory, we combine a data quality assessment algorithm in the PUEGM, which aims to remove low-quality data and improve the overall quality of user data. Finally, the optimal user revenue strategy under different conditions is obtained from the evolutionary stability strategy (ESS) solution and stability analysis. In order to verify the efficiency of the proposed solutions, extensive experiments using some real data sets are conducted. The experimental results demonstrate that our proposed method has high accuracy of data quality assessment and a reasonable selection of user revenue.
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Tao, Zongxia. "Cooperative Game Analysis based on Country Size and Market Position." Frontiers in Humanities and Social Sciences 2, no. 12 (December 21, 2022): 59–67. http://dx.doi.org/10.54691/fhss.v2i12.3132.
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This paper studies the cooperative game theory, and analyzes the cooperative game with international scale and market position. From the perspective of evolutionary game theory, this paper discusses the preconditions for big and small countries to participate in regional economic cooperation and the stability conditions of economic cooperation. This paper combines cooperative game theory with regional economic integration, and the economic and political alliance among countries can be regarded as a cooperative game. In order to analyze the cooperation of member countries, the countries are divided into small countries and big countries according to their size and market position, and the replication dynamic equation is calculated, then the basic conditions of the strategy of big countries and small countries participating in regional economic alliance are obtained, and the strategy selection probability of participants under the conditions of equilibrium strategy and non-equilibrium strategy is analyzed. In addition, using evolutionary game theory and Jacobian matrix to analyze the stability of local equilibrium point, a reciprocal game model of regional economic cooperation between big and small countries is established. Through the research, it is found that the necessary condition for the formation of regional economic integration is the economic complementarity among the cooperative parties, and the sufficient condition is that the cooperative parties can coordinate the distribution of interests among themselves through effective consultation and finally reach a binding agreement on the distribution of interests, thus restricting each other's economic behavior.
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Xin, Fangkun, and Zijing Wang. "Research on the Evolutionary Game Model and Stable Strategy of Urban Management Law Enforcement." Complexity 2022 (September 14, 2022): 1–8. http://dx.doi.org/10.1155/2022/7538059.
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As a form of the informal economy, countries around the world have different policies towards street vendors. This paper constructs a law enforcement game model composed of the Chengguan, street vendors, and urban residents in China. Based on the evolutionary game theory, we achieved the evolutionary stable equilibrium points under complying with different constraint conditions by solving the replicator dynamic equations of parties in the dynamic system. Through the gradual stability analysis of the equilibrium point, the stable strategy of the evolutionary game can be calculated. It is found that the flexible law enforcement behavior of urban management departments plays an important leading role in urban street governance. Flexible law enforcement not only requires macro policy arrangements but also tests the executive wisdom of street bureaucrats.
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Al-Jaoufi, Mohammed Ahmed Ahmed, Yun Liu, Zhen-jiang Zhang, and Lorna Uden. "Study on Selfish Node Incentive Mechanism with a Forward Game Node in Wireless Sensor Networks." International Journal of Antennas and Propagation 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/8591206.
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In a wireless sensor network, some nodes may act selfishly and noncooperatively, such as not forwarding packets, in response to their own limited resources. If most of the nodes in a network exhibit this selfish behavior, the entire network will be paralyzed, and it will not be able to provide normal service. This paper considers implementing the idea of evolutionary game theory into the nodes of wireless sensor networks to effectively improve the reliability and stability of the networks. We present a new model for the selfish node incentive mechanism with a forward game node for wireless sensor networks, and we discuss applications of the replicator dynamics mechanism to analyze evolutionary trends of trust relationships among nodes. We analyzed our approach theoretically and conducted simulations based on the idea of evolutionary game theory. The results of the simulation indicated that a wireless sensor network that uses the incentive mechanism can forward packets well while resisting any slight variations. Thus, the stability and reliability of wireless sensor networks are improved. We conducted numerical experiments, and the results verified our conclusions based on the theoretical analysis.
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Stehel, Vojtěch, Marek Vochozka, Tomas Kliestik, and Vladimir Bakes. "Economic analysis of implementing VMI model using game theory." Oeconomia Copernicana 10, no. 2 (June 30, 2019): 253–72. http://dx.doi.org/10.24136/oc.2019.013.
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Research background: The article deals with implementing VMI between the supplier and customer. To assess whether the system will be implemented, the evolution game theory is used. The contribution is based on the limitations of the study of the evolutionary game theory approach to modelling VMI policies (Torres et al., 2014) and its later extension, The evolutionary game theory approach to modelling VMI policies (Torres & García-Díaz, 2018). It aims is to complement the studies and provide a comprehensive picture of the issue.
Purpose of the article: The main objective of the contribution is to respond to the question whether the VMI system will be introduced between the supplier and customer.
Methods: In the first phase, the matrix is analysed from the point of view of the game meaning and its limit parameters. The limit parameters are set taking into account the economic reality. The only examined states of the matrix are those where the result is not obvious. For the purposes of the contribution, we work with a 5-year period. A new software capable of calculating evolutionary focus and their stability is created. Sensitivity analysis is carried out for the individual parameters that affect the system behaviour.
Findings & Value added: Value added is a complex description of the system and complementation of previous studies in this field. VMI is confirmed. The results obtained can be used for practical management, so that the managers are able to identify what the actual costs are and what the probability of introducing the sys-tem is. At the same time, they can identify the parameters that can be influenced by them and observe their impact on the shift of the system introduction probability.
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Wang, Qiwei, Qiang Mei, Suxia Liu, and Jingjing Zhang. "Analysis of Managing Safety in Small Enterprises: Dual-Effects of Employee Prosocial Safety Behavior and Government Inspection." BioMed Research International 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/6482507.
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This paper aims to promote a national and international occupational health and safety (OHS) intervention for small and medium enterprises (SMEs) within internal and external resources. Based on the characteristics of small SME management, the work environment and occupational health may be positively affected by the dual-effects of employees and government. Evolutionary game theory is utilized to identify relevant interactions among the government, small enterprises, and employees. Furthermore, dynamic simulations of the evolutionary game model are used to explore stability strategies and to identify modes of equilibrium.