Game Theory Model Research Articles

A model based on the evolutionary game theory for implementing green mining principles in riverine sand and gravel resources

An evolutionary Game Theory (GT) model was presented to study the dynamics between the mine management and government for implementing Green Mining (GM) principles in riverine sand and gravel mines. In this regard, a game was planned in which the mine management is the executing agent, while the government acts as the supervisor. Investigating the performance of the proposed model, regulatory factors such as governmental incentives and penalties were introduced. In order to compare the results, the effects of regulatory measures on strategy changes by mine management were analyzed into two distinct scenarios: classical GT and evolutionary GT, which provide valuable insights into the complex interactions between mine management and government. The Shahed sand and gravel mine near the Kordan River in Alborz province, Iran, was selected as a case study to validate the developed GT models. The results obtained from the classical GT model showed that a fine of $ 0.2 per tonne and a 30% governmental incentive for the mining and equipment costs, may encourage the mine management to choose the GM strategy. Conversely, the results of the evolutionary GT model indicated that by increasing the government subsidy from 30% to 50%, the rate of encouraging the mine management to choose the GM strategy could be accelerated. This situation is similar to the government incentive for mine management in case of fines from $0.2 to $1 per tonne. According to the results of the evolutionary GT model, when the population ratio increases over time, the selected strategy is more compatible and powerful compared to other ones. Therefore, it is concluded that the mine management in Shahed mine may turn to the GM strategy by imposing a penalty more than $0.6 per tonne.

The encroachment strategy under eco-innovation collaboration with delayed realized efficiency information

PurposeEco-innovation products, which means achieving more efficient and responsible use of resources and reducing the detrimental impact on the environment, can win a competitive advantage for the enterprises. But it is not easy to implement due to the high cost of eco-innovative technologies development, the uncertainty of market needs and return risk of investment. Many enterprises seek collaborations from their upstream suppliers to jointly carry out eco-innovation, such as Apple, IBM and Nike. A unique feature of collaboration is that efforts by one party enhance the marginal value of the other party's efforts. However, the collaboration will make the partner know the eco-innovation technology and prompt the partner to encroach the market to sell competitive products by herself. Motivated by this observation, this paper considers the optimal collaboration strategy on eco-innovation between upstream and downstream supply chain member and the optimal encroachment strategy of upstream supplier in a supply chain.Design/methodology/approachThis paper models a supply chain wherein a supplier provides products or materials for her manufacturer and cooperates with her manufacturer in eco-innovation. Also, the supplier could encroach on the market to sell similar products by herself. Then this paper uses game theory and mathematical modeling to do relative analysis.FindingsThe analysis reveals several interesting insights. First, eco-innovation collaboration makes supplier encroachment no longer only rely on the encroachment cost. The delayed realized eco-innovation efficiency information also plays a vital role. Second, different from previous research, the authors find the manufacturer's preference for supplier encroachment depends on the uncertainty of eco-innovation efficiency and potential market demand. Third, both partial and full encroachment strategies of the supplier can effectively improve the eco-innovation level.Originality/valueThe paper is the first to take the interplay between collaboration and encroachment into account in a supply chain. The results caution enterprises and policymakers to take vertical collaboration and delayed realized information into account in the competitive supply chain before making any operational decisions. Furthermore, the authors propose that governmental intervention aimed at stimulating supplier encroachment in appropriate circumstances can contribute to the improved environmental performance of products.

The embodiment and influence of game theory in the choice between the realization of self-worth and social value in life

Abstract The application and influence of game theory in the choice between achieving self-worth and social value in life. Different game rules dictate the decision to maximize self-interest, and self- and social values are considered to reach the Pareto optimal state. A reasonable allocation of self-value and social value is achieved using the crosswalk game as a reference. The results show that using the game theory model can yield a maximum value of 0.0001 for the rate of change, indicating an interaction between life self-value and social value, which helps to make subsequent timely responses to improve self-cultivation and strengthen normative behavior.

Perceived Online Tax Compliance Measures on Tax Compliance among Online Traders in Kenya

In several developing countries, tax collection by government relied on manual taxation, but there is now more drive towards introduction of electronic online filling of taxes. In Kenya, online tax system relies on integrated tax system known as iTax system. This study determined the relationship between online tax system and tax compliance among online traders in Uasin Gishu in Kenya. The study is based on three theories as part of the theoretical framework, that is, the Technology Acceptance Model (TAM) Theory and Game Theory Model of Equilibrium in Tax Compliance. The research study adopted a positivist research paradigm and explanatory research design. Primary data were collected using online questionnaires from a sample of 160 online traders respondents in Uasin Gishu. The study found that during the response to five attributes of tax compliance, the there was low levels of tax compliance. The study also reported low levels of perceived iTax security concerns as well as perceived tax system stability. The multiple linear regression coefficient (R2 = 0.863, P < 0.001) was positive indicating a positive correlation between perceived iTax security and perceived tax system stability with tax compliance. We conclude that perceived security risks concerns and perceived tax system stability affected tax compliance among online traders in Uasin Gishu County. Based on the findings, it is suggested that policy makers should not just place emphasis on technology but pay more attention on the characteristics of potential iTax users, e.g. their perceived security and system stability while implementing iTax service.

Dynamic Signal priority of the self-driving bus at an isolated intersection considering private vehicles

The transit signal priority leads to the delay of private vehicles in the priority and non-priority phases. To address this problem, a bi-level programming model is proposed based on the dynamic cycle and arrival rate of private vehicles under connected environment. The upper model is built by a delay triangle, with the maximum delay reduction of private vehicles between the decreased delay and increased delay in the experimental period. The lower model is constructed based on the Stackelberg model of game theory, and the objective is to obtain the dynamic cycle. A genetic algorithm (GA) is implemented to solve the proposed model. Based on SUMO, a case study of a self-driving bus in the city of Zhengzhou is conducted to demonstrate the effectiveness of the proposed model. The results from GA and SUMO are consistent, which verifies the effectiveness of the proposed model. The delay of the private vehicles with dynamic signal priority declines by 21.32% on average compared to that without priority. Compared with active signal priority, it declines by 22.63% on average. The proposed method is compared with the method proposed by other papers, and the delay per private vehicle is small. The effectiveness of the proposed method is further illustrated. The proposed methodology is helpful for improving the operation efficiency of intersections with minimum delay.

Current Situation and Prospect of Game Theory based Network Security Methods

The attack and defense model of network security based on game theory has developed into an effective network security model. It is a hot topic in the field of network and information security to use the idea of game theory to attack and defend the network security. This paper analyzes the general model of game theory in the field of security. This paper also analyzes the general model of network security attack and defense game. This paper also analyzes the game theory model of cryptographic protocol. This paper studies the existing network security methods based on game theory, reviews the development and evolution process and technical core of network security based on game theory, and compares the specificity of network security models based on game theory. Finally, the paper discusses the problems in the field of network security based on game theory, and tries to forecast its future development trend.

Risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM (1,1) model is employed to predict risk values for 2022–2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decision-making recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

Optimization game study of long-term dispatch for combined electricity and gas operation considering integrated demand response

The combined operation of electricity and gas is an important way of an integrated energy interconnection in the future. To meet the demands of multiple interests in the joint operation of electricity and gas, the master-slave game theory model is developed. In game model the power supply company and the gas company are the master players and the household load aggregation cluster is the slave player. The multi-energy joint load characteristics of household load aggregation and the uncertainty of the price demand response are used to obtain a payment function for each party to the game. The master-slave game model is built with the objective of maximizing the benefits on the supply side and minimizing the payments on the demand side. The master uses price as the strategy set and the slave uses demand response as the strategy set. The tripartite game equilibrium solution is screened by an optimal response function combined with Non-dominated sorting genetic algorithm (NSGA). Through the simulation analysis of an example, the frontier solution set of the tripartite game is obtained. Subjective scoring method and K-means clustering algorithm are used to select the optimal solution and discuss the application of the model under the influence of photovoltaic and gas turbine, the application of master-slave game and traditional NASH equilibrium solution, the application of game and general objective optimization in this paper. The model can be used to optimize the economic benefits of the parties in the long-term operation dispatch, and provide a reference for the optimal operation of market decisions under energy interconnection.

A Game Theoretic Approach to Collaboration in Policy Coordination

Public policies are courses of action by a government in response to public problems in the real world with the aim of meeting the needs of society. Such policies must be coordinated to avoid inefficiencies. Most attempts to model public policy coordination are qualitative and, therefore, do not yield precise conclusions. More accurate modelling attempts are found in game theory, but they are not entirely appropriate as models of policy coordination, because policy coordination involves a high degree of collaboration. There is only one game-theoretic model of collaboration, and it does not model public policy coordination. The aim of this article is to show that a collaboration-based game theory model is not only feasible, but also more realistic than current game theory models of policy coordination. This was performed by adapting Newton’s seminal model to a society capable of formulating and coordinating policies. When this adapted game was compared to alternative games used to explain policy coordination, it was found that the adapted game made more realistic assumptions, the modelling process was simpler, and it can be applied to a broader range of contexts. By demonstrating that the adapted model offers a feasible theoretical foundation for the modelling of policy coordination, this paper provides a starting point for future modelling efforts in this area.

Interpretable artificial intelligence for advanced oxidation systems: Principle, operations and performance

Advanced oxidation processes have been widely studied and employed due to their potent mineralization capacity for pollutants. However, the intricate reaction mechanisms of these processes pose limitations for fitting and predicting performance. In this study, we comprehensively derived and assessed neural networks for three advanced oxidation methods: catalytic oxidation, catalytic wet air oxidation, and electrochemical oxidation. Our analysis encompassed multilayer perceptron principles, forward and back propagation process, strategies for handling overfitting, and performance evaluation matrices. Additionally, we utilized Bayesian optimization to probe the impact of network architecture on outcomes. Two conventional methods, multiple linear regression and response surface methodology, are employed for comparison. Our results demonstrate that neural networks exhibit more robust performance in fitting and predicting advanced oxidation processes as indicated by statistical indicators. Importantly, we tackle the "black box" issue of neural networks by incorporating the shapley additive explanations interpretable model of game theory to elucidate the impact of advanced oxidation features on outcomes. The superior performance of explainable artificial intelligence techniques implies their vast potential for broad applications in environmental science and technology.

Strategic logic of unilateral climate intervention

Climate change and unabated greenhouse gas emissions are increasing the possibility that the world will turn to climate intervention to curb ever-increasing global temperatures. This paper uses game theory to elucidate the conditions that might make a state more or less likely to begin unilateral, as opposed to internationally coordinated, climate intervention (UCI). We solve this game for several specific scientific, economic, and climatological conditions that change the likelihood of a government starting its own climate intervention deployment program without the participation of the broader international community. Specifically, we demonstrate that the plausibility of UCI is linked to perceptions of three key elements: (1) the effectiveness of climate intervention strategies, (2) the sensitivity of specific governments to punishment by other states, and (3) satisfaction with climate and weather in the present. We conclude by discussing how this formal game theory model informs the design of future Earth system model simulations of UCI, international agreements related to climate intervention, and the development of solar climate intervention technologies.

A framework of payments for water-related ecosystem services (PWES) based on green water management

Green water describes precipitation that infiltrates into the unsaturated soil layer and returns to the atmosphere via plant transpiration and soil evaporation, which are two functions of the hydrological cycle. Green water provides the basis for timber growth, crop production, and ecosystem services. However, it has not been adequately accounted for in traditional payments for water-related ecosystem services (PWES), which predominantly consider on blue water and hence underestimate the availability of all water resources. In this study, a new framework of payments for green water-related ecosystem services (PGWES) is proposed based on green water management (GWM) and green water compensation (GWC). This framework is constructed with game theory modelling, hydrological simulation and scenario evaluation. Then, the Xiangjiang River Basin (XRB) is used as a case study to test and evaluate the feasibility of the framework. The results of this study are as follows: (a) the framework of PGWES and its game payoff matrix and optimal payoff function are improved by adding the GWM scenarios. This approach can identify the GWC standard and Pareto optimal solution in different GWM scenarios, thereby optimizing the spatial allocation of blue and green water in the river basin and coordinating conflicts of interest between the upstream and downstream. (b) The average Pareto optimal payoffs of the XRB are increased by 4390 million CNY/year under different GWM and GWC scenarios compared to the baseline scenario, and the average GWC standard is 2.41 CNY/m3 or 1305.98 CNY/hm2. The case study indicates that the socioeconomic and ecological benefits for the whole XRB are expected to significantly improve under this framework. (c) Three aspects of managing water resources and conflict of interest issues noted during the study include “broadening water sources”, “saving water resources” and “coordinating water conflict”. Green water resources are an important component in broadening water sources; green water management provides a basic measurement tool for saving water resources; and green water compensation based on game theory offers a possible way to coordinate water conflicts and should be given more attention. In general, the PGWES framework provides a referenced methodology for the efficient development and equitable allocation of blue and green water resources in the river basin; furthermore, this study provides a scientific basis for the theory and methods of PWES, thus enriching this field of research.

A tripartite evolutionary game analysis of providing subsidies for pick-up/drop-off strategy in carpooling problem

Although the pick-up/drop-off (PUDO) strategy in carpooling offers the convenience of short-distance walking for passengers during boarding and disembarking, there is a noticeable hesitancy among commuters to adopt this travel method, despite its numerous benefits. Here, this paper establishes a tripartite evolutionary game theory (EGT) model to verify the evolutionary stability of choosing the PUDO strategy of drivers and passengers and offering subsidies strategy of carpooling platforms in carpooling system. The model presented in this paper serves as a valuable tool for assessing the dissemination and implementation of PUDO strategy and offering subsidies strategy in carpooling applications. Subsequently, an empirical analysis is conducted to examine and compare the sensitivity of the parameters across various scenarios. The findings suggest that: firstly, providing subsidies to passengers and drivers, along with deductions for drivers through carpooling platforms, is an effective way to promote wider adoption of the PUDO strategy. Then, the decision-making process is divided into three stages: initial stage, middle stage, and mature stage. PUDO strategy progresses from initial rejection to widespread acceptance among drivers in the middle stage and, in the mature stage, both passengers and drivers tend to adopt it under carpooling platform subsidies; the factors influencing the costs of waiting and walking times, as well as the subsidies granted to passengers, are essential determinants that require careful consideration by passengers, drivers, and carpooling platforms when choosing the PUDO strategy. Our work provides valuable insight into the PUDO strategy’s applicability and the declared results provide implications for traffic managers and carpooling platforms to offer a suitable incentive.

Optimal investment policy in sharing and standalone economy for solar PV panel under operational cost

The transition to sustainable energy sources, driven by the need to address climate change and resource depletion, has led to the increasing adoption of renewable energy technologies. Among these sustainable alternatives, solar energy stands out prominently. Harnessing the power of the sun aligns with various Sustainable Development Goals (SDGs) by providing clean and affordable energy, promoting climate action, and supporting sustainable communities. Solar PV panels face challenges despite their advantages, including susceptibility to natural disruptions like hurricanes, hailstorms and extreme temperatures. In 2019, the solar energy sector experienced a stark contrast in losses, with average solar losses resulting from conventional natural disasters or severe weather conditions being nearly 24 times higher than the average losses unrelated to weather events. Furthermore, a significant 70% of solar losses within the past decade have emerged since 2017. Similarly, in 2019 hail storm damaged more than 400,000 solar panels and caused insurance losses totaling $70 million in Texas. The research addresses the effect of natural disruptions on investment decisions. It explores the viability of a sharing economy business model that allows multiple participants to collectively invest in solar PV systems and share the benefits to ensure the future expansion of solar PV installations. The study formulates the problem as a game theory model to strategize and find optimal solutions for both the standalone economy and sharing economy scenarios, considering operational costs, net metering and the unpredictability of natural disasters. By providing valuable insights into the dynamics of the PV market with the help of computational results, the research aims to enhance the resilience of solar installations and promote sustainable energy practices. Through this work, individuals and communities can make informed investment decisions, contributing to a cleaner, greener and more sustainable world.

The selection of sales channels considering consumer behavior preferences in a co-branding strategy

As a marketing strategy, co-branding has become popular among brand manufacturers in recent years. Unlike previous studies on co-branding, we extend the research from manufacturer-to-manufacturer coopetition strategies to a platform-based supply chain. This paper builds two game theory models involving two manufacturers and one online platform, and divides consumers into Mavericks and Herds, who seek uniqueness and uniformity, respectively, and discusses the channel selection and the market positioning strategy. Some interesting findings are obtained, first, the equilibrium decisions are improved and the optimal profits are enhanced by considering the upstream and downstream cooperation. Second, the online retail channel is chosen when the revenue-sharing ratio is medium and the commission rate is low. Third, brand manufacturers have more opportunities to choose the online retail channel when the co-branded product is marketed to Herds, which is summarized as the market segmentation effect.

Game Analysis on Supervision of live goods problem with Tiktok Platform Participation including the absence of Lemon market

With the internet and technology development, the utilization rate of short video platforms has gradually increased, and online shopping has become very common. On September 20, 2016, Tiktok short video platform was launched. A TikTok mall is a delivery tool provided by Tiktok e-commerce for merchants. The platform reduces the threshold for merchants to meet the requirements and implements a comprehensive opening policy to obtain more user traffic. Inevitably, lowering the threshold brings the disadvantage of merchants selling fake and inferior products, leading to the lemon for the market and significantly impacting the platform atmosphere and user traffic. Based on the idea of mixed strategy and a journal about the online game theory of product quality, this paper adds more variables, taking into account the negative impact of Tiktok's actual scheme policy and lemon market. Constructing a game theory model including merchants and Tiktok regulatory department, analyze its nash equilibrium and derivative of each variable. Finally, find out that the lemon market exists on the Tiktok platform. Second, the higher cost of high-quality firms leads to strengthening supervision to prevent the low-quality firms from being driven out of the market. Third, the lower profit of low-quality goods, the merchants prefer to sell high-quality goods. The strategies selected by the regulatory authorities on the Tiktok platform and the strategies of the merchants are influenced by the production costs of different quality, the regulatory costs, and the rewards obtained from the efforts made by the regulatory authorities in sampling inspection. These factors will also influence their profits. This paper will prove the conclusion with accurate data.

A Game Analysis on International Emissions Trading under Climate Change

Carbon emissions and climate are intricately related. People's activities are growing as a result of advances in science and technology, which raises carbon dioxide emissions. As a result of these greenhouse gases, the atmosphere's ability to dissipate heat will decline, raising global temperatures and making climate change a more serious issue. To achieve sustainable development, people must begin to pay attention to these challenges and strike a balance between the environment and economic progress. This paper introduces the mechanism of emissions trading and the benefits of its operation. In order to discuss the possibility of enabling countries to use emissions trading, this paper uses a non-cooperative game theory model to analyze the choices made by developing and developed countries under the background of the Kyoto Protocol. Combined with the equilibrium obtained by the hypothesized model, some methods and reasons for improving the results are proposed. This paper concludes that both developed and developing countries are more inclined to use emissions trading to achieve emission reduction targets or obtain certain benefits.

The Effect of Environmental Administrative Punishment on Water Pollution: An Analysis from the Perspective of Game Theory

The water resource pollution in China is very serious, and as a kind of public goods, water resource is easy to cause "free riding" behavior in the process of consumption. How to eliminate the interest conflict between different economic subjects? Environmental administrative punishment is one of the answers. This measure based on the Pigou theory is the foundation of Chinas environmental governance. From the perspective of game theory, this paper analyzes the effect of administrative punishment means of the water resources environment by constructing and analyzing the game theory model and concludes: that the unreasonable setting of the administrative punishment system for the water resources environment and the incomplete implementation process make its effect poor. Finally, the paper puts forward improvement suggestions from three aspects: strengthening supervision, system innovation and the application of Coase theory.

A New Approach to the Battle of Magnesia (190 BCE): A Game Theory Model

Doğuda güçlü bir kral olarak ortaya çıkan Seleukos kralı III. Antiokhos’un yaklaşık kırk yıllık saltanatı boyunca krallığının sınırlarını Syria’dan batıya doğru genişletmesi, Akdeniz ve Ege civarındaki faaliyetleri, Hellas’a müdahalesi ve Roma müttefiki kentlere yaptığı saldırılar birtakım gelişmeleri beraberinde getirmiştir. MÖ 190 yılında Romalılar ve müttefiklerinden oluşan orduyla, Seleukos kralı III. Antiokhos önderliğindeki güçler Magnesia’da karşılaşmışlardır. Bu çalışmanın amacı, Kromayer’in belirttiği savaş alanı ile ilgili yeni bir öneride bulunmak ve savaşa dahil olan aktörlerin davranış biçimlerini, alternatif stratejilerini göz önünde bulundurarak Magnesia Savaşı’nın oyun teorisi bağlamında ele alınıp alınamayacağını sorgulamaktır. Bu kapsamda iki oyuncu ve ikişer hamle seçeneğinden oluşan ardışık ve sıfır toplamlı bir oyun modellenmiş ve oyun teorisinde yer alan geriye doğru çıkarsama ve domine edilmiş stratejilerin elenmesi gibi denge çözüm yöntemleri ile bir analiz yapılmıştır. Analiz neticesinde Romalıların dominant stratejisinin her durumda savaşmak olduğu tespit edilmiş, Seleukosların ise tarihte yaşananın aksine savaştan kaçınmasının optimal hamlesi olduğu oyun teorik bağlamda elde edilmiştir.

A robust multiple Unmanned Aerial Vehicles 3D path planning strategy via improved particle swarm optimization

Path planning algorithms for Unmanned Aerial Vehicles (UAVs) are essential in various domains, such as search and rescue operations, agriculture, and delivery services. Nonetheless, finding optimal flight paths in complex environments with obstacles remains challenging. This paper proposes a novel path planning algorithm that uses a Nash equilibrium approach based on game theory to strike a balance between the exploitation and exploration capabilities of UAVs. The algorithm is designed in a simulated flight environment with obstacles, utilizing the self-awareness and group awareness coefficients from particle swarm optimization(PSO) as participants in the game theory model. The proposed path planning algorithm significantly improves the navigation of multiple UAVs in complex scenarios with obstacles by achieving a balance between their exploitation and exploration capabilities. Simulation experiments demonstrate that the proposed method surpasses traditional approaches, exhibiting an average improvement of 32.57%, 32.17%, and 29.33% in the algorithm convergence time, average flight distance, and average flight time, respectively. The significance of this research lies in its contribution to advancing UAV path planning algorithms. By integrating game theory and PSO, the proposed method optimizes the exploration and exploitation capabilities of UAVs, leading to improved navigation and resource utilization.