Dynamic Game Research Articles

An Approach to Stochastic Dynamic Games with Asymmetric Information and Hidden Actions

An Approach to Stochastic Dynamic Games with Asymmetric Information and Hidden Actions

Evolutionary game analysis of cooperation strategies for core enterprises of film copyright import and export under China’s supporting policies

PurposeThis paper constructs a tripartite evolutionary game model between the government, the core enterprises of film copyright export and imports and uses the system dynamics model to simulate and find the optimal selection results of single and mixed government incentives under dynamic changes, aiming to promote the development of foreign trade of film copyright and innovation and development of the film industry so as to improve the overall social benefits of the film industry and provide policy enlightenment for enhancing the import power of foreign core enterprises to introduce domestic film copyrights.Design/methodology/approachIn this paper, a tripartite evolutionary game model of the government, the core enterprises of film copyright export and imports is constructed, the evolution process of cooperation strategy is derived, the impact of innovation income coefficient, mixed incentive policy and single incentive policy on the evolution results is analyzed, and the system dynamic model is used to simulate to find the optimal selection results of single and mixed government incentives under dynamic changes, so as to provide reference for the government’s dynamic incentive decision-making.FindingsThe results show that export-oriented core firms are more sensitive to mixed incentives, while import-oriented core firms respond more quickly to single incentives. The large innovation income coefficient has a negative impact on the willingness of import-oriented core enterprises to cooperate. The study proposes measures to increase the willingness of core companies to participate.Research limitations/implicationsDue to the fact that numerical simulation is based on simulation, there may be a certain gap between it and the actual situation. Therefore, it is necessary to further use actual data to conduct empirical analysis on the theoretical model.Practical implicationsThis article mainly focuses on analyzing the impact of strategy choices and related parameters of various entities on the incentive mechanism and studying the foreign trade cooperation strategies of film copyright export enterprises under policy support from a theoretical model perspective. Furthermore, research has proven that in order to effectively enhance the willingness of foreign import core enterprises to participate in the foreign trade of domestic film copyrights, the government needs to coordinate the use of single incentive policies and mixed incentive policies. This study provides a major contribution for policymaker to develop film copyright import and export trade.Social implicationsBased on the research conclusions, this paper puts forward management countermeasures to further improve the development of the film copyright import and export trade. The first is to enrich government incentive methods and stimulate the vitality of film copyright and foreign trade market entities. The second is to guide the core enterprises of film copyright export to increase investment in innovation and stimulate the endogenous driving force of industrial development. Finally, lengthen the foreign trade industry chain of film copyright and increase the income of film derivatives.Originality/valueFirstly, this paper applies the research methods of evolutionary game and system dynamics simulation to the field of foreign trade research on film copyright and expands the research perspectives and methods of the film industry. Secondly, by analyzing the “cost-benefit incentive” relationship of the evolutionary game of government export-oriented core enterprises and importing core enterprises, an evolutionary game model is constructed, the quantitative point of tripartite interest decision-making is solved and the research object of the evolutionary game method is expanded. Finally, the system dynamics model is used to simulate and find the optimal selection results of single and mixed government incentives under dynamic changes, so as to provide reference for the government’s dynamic incentive decision-making.

Sensitivity analysis for a dynamic macroeconomic policy game in a monetary union

In this paper, we examine the sensitivity of the results of an earlier paper which presented and analyzed a dynamic game model of a monetary union with coalitions between governments (fiscal policy makers) and a common central bank (monetary policy maker). Here we examine alternative values of the parameters of the underlying model to show how the earlier results depend on the numerical parameter values chosen, which were obtained by calibration instead of econometric estimation. We demonstrate that the main results are qualitatively the same as in the original model for plausible smaller and larger values of the parameters. For the few cases where they differ, we interpret the deviations in economic terms and illustrate the policies and their macroeconomic effects resulting from the change to the parameter under consideration for one of these cases.

How Cooperation and Competition Arise in Regional Climate Policies: RICE as a Dynamic Game

How Cooperation and Competition Arise in Regional Climate Policies: RICE as a Dynamic Game

Generative adversarial network based resource optimization for UAV jamming assisted cognitive covert communication

This paper discusses a resource optimization problem for unmanned aerial vehicle (UAV) jamming assisted cognitive covert communication. Specially, the secondary users adopt underlay strategy for spectrum access and the UAV transmits the noise signal to confuse the underlay detection of eavesdropper. According to the dynamic game characteristics in the covert communication process, a new generative adversarial network-based covert communication resource optimization algorithm (GAN-RO) is proposed for the joint optimization of UAV’s trajectory and power in cognitive covert communication assisted by UAV’s interference. The generator simulates the legitimate user to generate the resource allocation scheme, while the discriminator imitates the eavesdropper to detect covert communication. The dynamic game process between the generator and discriminator can obtain covert communication schemes by achieving Nash equilibrium. Simulation results indicate that the proposed GAN-RO algorithm can obtain a near-optimal resource optimization scheme with a rapid converge speed for non-ideal UAV jamming assisted cognitive covert communication system.

The Relationships Between Personality Traits and Online Game Playing Motivations Amongst College Students

As studies focusing on the psychological dynamics of multiplayer realistic battle games in Malaysia is quite limited, the present study attempts to investigate the relationships between personality traits and online game-playing (PUBG; Player Unknown’s Battle Ground) motivations amongst college students. A total of 200 students who are actively playing voluntarily answered the Mini-IPIP (Mini-International Personality Item Pool Scales) (Donellan et al, 2006) and Motivation for Play (Yee, 2006) to measure personality traits and types of motivation in playing online games. Descriptive and inferential analyses were conducted and the results indicated that the most prevalent personality traits among the players are Agreeableness followed by Extraversion. In addition, Escapism and Social are the strongest reasons reported for playing the PUBG. Males are significantly higher in Advancement, Mechanics, Customization and Discovery in-game motivation as compared to females. Significant correlations are found in a few analyses, namely Extraversion was positively related with Advancement motivation, and Agreeableness was positively related to Teamwork motivation. Lastly, Conscientiousness was positively related with Competition motivation. The results further supported the personality and in-game motivation for future research directions.

Fast or stable: Research on dynamic behaviors of duopoly automakers under the background of energy transformation in the automobile industry

New energy vehicles (NEVs) are crucial way to solving environmental and energy dilemmas. However, the transition from traditional energy vehicles (TEVs) to NEVs is extremely intricate. If the process for TEVs switching to NEVs falls into out order, the automobile industry will be shaken. This paper takes electric vehicles (EVs), representing NEVs, and internal combustion engine vehicles (ICEVs), representing TEVs, as research objects, and constructs a dynamic Gounod duopoly model for the production decisions of two oligopolistic automakers under the dual credit policy. Combining the nonlinear dynamic theory and Cournot game, the influence of policy, market, technology, and cost on the stability of duopoly automakers’ dynamic production game equilibrium and the nonlinear evolution characteristics of Cournot-Nash equilibrium are analyzed systematically. Results show that: (1) In the transition from ICEVs to EVs, if the speed of production adjustment is too fast, the automobile system would trap into chaos and shakeouts, and the social welfare would show volatility. (2) The revised dual credit policy increases the credit ratio and decreases the credit coefficient which enhances the stability of automobile system. This revision may accelerate the transformation from ICEVs to EVs in the automobile industry. Especially, the credit coefficient plays a more significant role. (3) The consumer acceptance for vehicle prices and the range of EV are positively correlated with the production of EVs and the social welfare, and negatively correlated with the production of ICEVs. Nevertheless, the cost of the two types of vehicle had the opposite effect compared price acceptance and range of EVs.

Go-Explore Complex 3-D Game Environments for Automated Reachability Testing

Modern AAA video games feature huge game levels and maps which are increasingly hard for level testers to cover exhaustively. As a result, games often ship with catastrophic bugs such as the player falling through the floor or being stuck in walls. We propose an approach specifically targeted at reachability bugs in simulated 3D environments based on the powerful exploration algorithm, Go-Explore, which saves unique checkpoints across the map and then identifies promising ones to explore from. We show that when coupled with simple heuristics derived from the game's navigation mesh, Go-Explore finds challenging bugs and comprehensively explores complex environments <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">without the need for human demonstration or knowledge of the game dynamics</i> . Go-Explore vastly outperforms more complicated baselines including reinforcement learning with intrinsic curiosity in both covering the navigation mesh and number of unique positions across the map discovered. Finally, due to our use of parallel agents, our algorithm can fully cover a vast 1.5km x 1.5km game world within 10 hours on a single machine making it extremely promising for continuous testing suites.

Is transparency a blessing or a curse? An experimental horse race between accountability and extortionary corruption

If it is disclosed to a citizen which public official handles her case, this creates accountability. If the official abuses her authority, the citizen can report this misconduct to higher authority, which can intervene. But transparency also makes it possible for a citizen to pressure an official to decide in her favor. We model this interaction as a sequential game, and define which behavioral effects are required for either effect to dominate. We test the game experimentally. Within the parameters of our experiment, transparency clearly trumps anonymity. If the abuse of sovereign authority risks going unchecked, the occasional retaliation against dutiful officials is, on balance, the smaller social cost.

Dynamic game analysis of E-commerce platform rewards and research & development investment of settled enterprises

Contributing to the literature on the E-commerce platform governance, this paper analyzes the e-commerce platform's optimal reward strategy and settled enterprises' optimal Research & Development (R&D) investment decision with different R&D patterns. The results indicate that the platform's rewards can increase settled enterprises' R&D investment and overall benefit of the ecosystem. Under R&D competition pattern, the platform's optimal reward is positively correlated with the technology spillover effect. Under R&D cartels and RJV competition patterns, the platform's optimal reward will increase as the degree of product complementarity. Under R&D competition pattern, settled enterprises' R&D investment and product quality reach the optimum.

The Complexities in the R&amp;D Competition Model with Spillover Effects in the Supply Chain

This study aims to investigate the research and development (R&amp;D) competition within the supply chain, focusing on two aspects: R&amp;D competition at the manufacturing level and competition in pricing strategies. This paper establishes a dynamic game model of R&amp;D competition, comprising two manufacturers and two retailers, with both manufacturers exhibiting bounded rationality. The key findings are as follows: (1) an increase in the adjustment speed positively affects the chaotic nature of the R&amp;D competition system, leading to a state of disorder. This chaotic state has adverse implications for manufacturing profitability. (2) The spillover effect exhibits a positive relationship with the level of chaos in the R&amp;D competition system. A greater spillover effect contributes to a more turbulent environment, which subsequently impacts the profitability of manufacturers. (3) R&amp;D cost parameters exert a positive influence on the stability of the R&amp;D competition system. When the system reaches a state of equilibrium, an escalation in the R&amp;D cost parameters poses a threat to manufacturer profitability. (4) Retailer costs play a detrimental role in the stability of the R&amp;D competition system. As retailer costs increase, there is a decline in R&amp;D levels, thereby diminishing manufacturer profitability. (5) To mitigate the chaotic state, we propose the implementation of the time-delayed feedback control (TDFC) method, which reflects a more stable state in the R&amp;D competition system.

A Tripartite Game Strategy to Promote the Commercialization of Research Results: A Synergistic Development Path Between Universities, Government, and Enterprises

Purpose – The purpose of this paper is to explore the tripartite relationship between the government, universities, and enterprises in the process of improving China’s innovation index. We hope to gain an in-depth understanding of the dynamic game process among these three, and how various factors affect the way they cooperate in this process. Design/Methodology/Approach – Based on evolutionary game theory as a research tool, we constructed a tripartite evolutionary game model of universities, government, and commercial institutions, and analyzed the stability of each party's strategic choices and the relationship between the influence of each element. Findings – By simulating strategy combinations and the evolution process in different contexts, we derived the conditions for the occurrence of stable strategy combinations among universities, governments, and business organizations. Through the above study, we found that stable strategy combinations among government, universities, and enterprises are crucial in promoting the development of China’s innovation index. Research Implications – This study has important theoretical significance for understanding the dynamic relationship among government, universities, and firms, and also provides practical guidance for policy makers. Through this study, policy makers can have a clearer understanding of the needs and interests of each party, so that they can formulate more effective policies to promote the development of innovation activities.

Dynamic game evolution complexity of new energy and fuel vehicle manufacturers under carbon cap‐and‐trade policy

AbstractConsidering customers' preferences for low‐carbon products, the paper delves into the short‐run and long‐run repetitive game involving three oligopolistic manufacturers engaged in the production of new energy vehicles (hybrid electric vehicles [HEV] and battery electric vehicles [BEV]) and conventional fuel vehicles (FV) within the framework of a carbon cap‐and‐trade policy (CaT). In the short‐run game model, this study explores the optimal decision of oligarchic manufacturers and analyzes the efficiency of the supply chain in the context of cooperation and non‐cooperation. In the long‐run repetitive scenario, the article examines the optimal decision of the manufacturer, assuming rational economic behavior aimed at maximizing individual profits within a non‐cooperation game strategy. Finally, the paper investigates the elements that influence the efficiency of the supply chain. The results reveal that (1) fuel vehicles possess greater flexibility in adjusting parameters compared to the other vehicle types; a judicious increase in manufacturers' price adjustment parameters in the stability domain is beneficial to their respective profits and enhances the overall supply chain profitability. (2) Maintaining customers' preference for low‐carbon products within a reasonable range is crucial for the mutual benefit of all manufacturers. (3) The government needs to allocate more carbon emission limits to fuel vehicle manufacturers in order to improve supply chain efficiency.

On breadth and depth of climate agreements with pledge-and-review bargaining

This paper analyzes the effects of partial cooperation on the breadth and depth of climate agreements in dynamic games in which countries emit, invest in green technology, decide to participate in a climate coalition and participants negotiate the contract duration. When choosing emissions reductions (pledges), coalition countries apply Harstad’s (2023a) pledge-and-review bargaining and partially cooperate. We distinguish between stock-independent and stock-dependent investment costs. It is shown that narrow-but-deep agreements may be welfare superior to broad-but-shallow agreements for signatories. In addition, if the degree of partial cooperation is sufficiently high, broad-and-deep agreements and even first best can be achieved.

Research on collaborative innovation cooperation strategies of manufacturing digital ecosystem from the perspective of multiple stakeholders

The digital ecosystem has hastened the fusion of manufacturing and digital technology in realizing product and service value. However, due to the coordination dilemmas within the digital ecosystem such as risk sharing, competition and cooperation among stakeholders, this study aims to explore the collaborative innovation cooperation strategies of multiple stakeholders, and to investigate the interaction effects of differential incentives on each other's strategies. By constructing a dynamic differential game model, this study solves the optimal innovation efforts, digital servitization levels and innovation benefits under different cooperation intensities, and analyzes the influence of various factors on the total innovation benefits of the digital ecosystem. It is found that under different decision-making modes, the influence of incentive subsidy coefficient and cost-sharing coefficient on the innovation efforts and innovation benefits of multiple stakeholders is different. Under the decentralized decision-making mode, the incentive mechanism positively promotes the innovation efforts of both parties of cooperative enterprises, while the local government is not affected, while under the centralized decision-making mode, the incentive mechanism positively affects the innovation efforts and innovation benefits of all three parties. Specifically, under the Stackelberg game, both the innovation efforts and innovation benefits achieve Pareto improvement, while under the cooperative game, the total system innovation benefits reach Pareto optimality and the optimal strategy is realized. In addition, an optimal range exists for the benefit distribution coefficient and the policy guidance coefficient. Furthermore, factors like the cooperative benefit impact coefficient, innovation capability coefficient, and policy guidance coefficient have a positive effect on the total system innovation benefits. Conversely, factors like the discount rate, technology decay coefficient, and innovation input coefficient inhibit the growth of the total system innovation benefits. The value provides theoretical support for collaborative innovation cooperation in the digital ecosystem, thus facilitating the progress of digital transformation in manufacturing.

Revolutionary leaders and the punishment of critics

I explore a previously neglected mechanism of mass mobilization in autocracies. Revolutionary leaders may deliberately provoke punishment from the incumbent regime to signal their political conviction and thus encourage citizens to identify with and support the revolutionary movement. I model the interplay of repression, criticism, and revolutionary actions as a dynamic game with incomplete information about the leader’s type. The role of the revolutionary leader is to enable people to identify with the movement by credibly embodying political change. From the incumbent’s perspective, repression turns out to be a double-edged sword. On the one hand, a severe punishment of critics increases citizens’ cost of participating in revolutionary actions. On the other hand, harsh repressions may simultaneously establish a trustworthy leader whom people want to follow in order to replace the current political regime. My results thus help explain a stylized fact, namely that revolutionary leaders sometimes need to fail before they can succeed.

Entrepreneurial spirit: A catalyst on the road to green and sustainable development——A theoretical analysis based on dynamic games and empirical tests from Chinese data

Environmental protection and sustainable development are now profoundly ingrained in the public consciousness in the modern era of the global green revolution. First, this paper uses an evolutionary game model to theoretically analyse the impact of environmental regulation and green finance on enterprises by dissecting the game behaviour between local governments, banks and enterprises. Then, we incorporate entrepreneurial spirit into the model to determine whether entrepreneurial spirit accelerates the achievement of green sustainability objectives. Environmental regulation and green finance are found to contribute substantially to the innovation of green technologies by local enterprises, while entrepreneurial spirit accelerates this process. Finally, we empirically test the findings based on a prefecture-level panel dataset from 2007 to 2020. We find that green finance has a positive impact in Central and Western cities of China, while Eastern cities are in greater need for government environmental regulation controls. For entrepreneurial spirit, the incentive effect of entrepreneurial spirit on the level of green technology innovation is more significant in Central and Western regions of China. This paper enriches the field of research on entrepreneurial spirit and regional green sustainable development by providing empirical evidence for the evaluation of environmental regulatory and green financing policy impacts.

Exploring Pattern Mining with FCM Algorithm for Predicting Female Athlete Behaviour in Sports Analytics

In the changing field of sports analytics, examining and predicting athlete behaviour is crucial for improving performance and reaching the best results. As data analysis becomes more important in sports, using pattern mining methods is critical to discovering meaningful patterns and trends in the large datasets used in sports analysis. This study proposes a Performance Optimization Framework for Female Athletes (POFFA) that explores the field of sports analytics to examine how pattern mining methods, explicitly using the Flexible Fuzzy C-Means (FFCM) algorithm, can help predict female athlete behaviour. This study aims to offer detailed insights into behavioural patterns that can help improve coaching techniques, training schedules, and performance improvement procedures by concentrating on female athletes. The study intends to provide a deep understanding of female athlete behaviour and game dynamics using the FCM approach, known for its effectiveness in dealing with complex, sparse, multi-objective optimization difficulties. The results of this study can enhance the field of sports analysis by providing detailed insights into the behavioural patterns displayed by female players in many sports categories. By combining pattern mining methods with the FCM algorithm, this study introduces a thorough process for examining and predicting athlete behaviour in sports analytics. In the end, the results of this study have practical significance for coaches, trainers, and sports professionals, offering helpful advice for improving the performance of female athletes in competitive sports settings. By using data-driven insights from pattern mining analyses, individuals in the sports business can improve their plans and interventions to enhance female athletes' athletic potential and overall performance results.

The application of artificial intelligence in the game field

With the rapid development of artificial intelligence technology, its application in the field of games is increasingly widespread. At present, the application of artificial intelligence in games has become a research hotspot. This article mainly explores the application of AI in various types of games such as first person shooter (FPS), Role playing Games (RPGs), Strategy, and analyzes their advantages and disadvantages based on the category of the game. Specifically, this article explores the application of AI in FPS games, focusing on how AI controls the behavior and strategies of enemies to provide players with challenging and realistic experiences. In the context of RPGs, the paper analyzes AI's impact on intelligent decision-making and interaction with non-playable characters (NPCs). Intelligent NPCs create a more authentic and immersive interaction between players and game characters. In the case of strategy games, AI enhances the strategic and challenging aspects, offering a more layered and dynamic gaming experience, and pushing players' decision-making abilities and strategic thinking. Additionally, the article discusses the limitations and challenges of AI in games. This paper summarizes and prospects the application of AI in the field of games.

Tariff Hedging with a New Supplier? An Analysis of Sourcing Strategies Under Competition

Due to the U.S.-China trade war, multinational firms may develop new contract manufacturers outside China to hedge against high tariffs on Chinese exports to the U.S. market. However, tariffs exhibit high uncertainty in recent years and developing a contract manufacturer incurs costs; hence, it is challenging to decide whether to develop a new contract manufacturer. We study two competing firms’ contract manufacturer development decisions in a sequential game. First, we find that multinational firms prefer to develop new contract manufacturers when tariffs are expected to rise moderately rather than sharply. This is because the value of developing a new contract manufacturer for a multinational firm is the largest when the new contract manufacturer and the existing one compete most intensely, which happens for similar tariff-inclusive costs. This implies, when taking into account competition, an overly high tariff on Chinese exports to the United States does not necessarily serve the purpose of switching suppliers from China to other regions. Furthermore, higher tariff uncertainty can decrease development value and hence the incentive to develop a contract manufacturer. When there is an upward tariff shock that induces the equilibrium where both multinational firms develop a contract manufacturer, both firms must be worse off; only when it induces the asymmetric development equilibrium is it possible for the multinational firm developing a contract manufacturer to be better off, even with tariff increase and development cost. Second, the impact of development cost on multinational firms’ incentives to develop new contract manufacturers is nonmonotone. As the development cost increases, the equilibrium can switch from both not developing new contract manufacturers to one developing a new contract manufacturer. Third, when the future tariff is expected to be high, multinational firms should diversify their development strategies in environments with fierce competition. Furthermore, increasing competition is not necessarily harmful for multinational firms. We also extend the analysis to consider asymmetric development costs and unobservable wholesale prices, and find the major insights are robust.