Dynamic Game Theory Research Articles

Alternative Method to Resolve the Principal–Principal Conflict—A New Perspective Based on Contract Theory and Negotiation

Liquidated damages mechanisms have been analyzed from a legal perspective and applied to real-world contracts. Due to the lack of application of LDs to common agency theory, this research explores whether the liquidated damages mechanism can resolve principal–principal conflicts under common agency. We combine the moral hazard model of common agency with non-cooperative dynamic game theory to analyze the influence of the liquidated damages mechanism on the agent and principals under the condition of complete information and incomplete information. We find that liquidated damages are the key factors affecting the optimal contract between the principal and agent. Since the agent does not terminate the current contract, a principal–principal conflict arises when another principal wishes to enter into a new contract with the common agent. We find that the agent terminates the existing contract and signs a new one with another principal. The injured party requires liquidated damages from the breaching party. Therefore, they will negotiate the number of liquidated damages. Liquidated damages cause the bargaining game to generate a unique subgame perfect Nash equilibrium and sequential equilibrium. We prove that only when liquidated damages belong to a specific interval does a mechanism generating the Pareto optimal solutions to solve the principal–principal conflicts under common agency exist. A common way to resolve this conflict is ensuring that the minority is subordinate to the majority. For the first time, we study how the liquidated damages mechanism solves multi-principal conflict. This is another perspective that can be used to solve the conflict. Therefore, our paper expands the method of resolving the conflict and extends the theory of common agency; we first show the delegation process. Our research can be applied to various situations and provide a rational decision-making basis for participants.

Progressive system safety and reliability analysis: A sustainable game theory approach

AbstractThis research aims to study the applicability of game theory to system safety and reliability decision‐making problems and corresponding objective conflicts using non‐cooperative games. The non‐cooperative games would solve the games considering non‐cooperative cognitive decision‐makers behaviors, which are commonly ignored by other system safety and reliability analysis (SSRA) techniques, assuming that there would be perfect cooperation between the players (decision‐makers). Game theory can also recognize and understand the decision‐makers' behaviors and provide a “win‐win” situation for all players and the best broader system outcomes. The paper also shows the use of dynamic game theory in system safety and reliability decision‐making problems over time. The results indicate the effectiveness and efficiency of game theory and show how this can better reflect decision‐makers’ opinions in system safety and reliability decision‐making problems.

Retraction Note: Development trend of sharing economy in big data era based on duplication dynamic evolution game theory

Retraction Note: Development trend of sharing economy in big data era based on duplication dynamic evolution game theory

Influence of public credit risk on private capital in public–private partnership models

AbstractPublic credit risk is an important factor in private capital's decision to participate in public–private partnership (PPP) projects. We explore why private capital participates in such projects using dynamic game theory. We assess the framework of credit rating agencies assessment of local fiscal risk and construct a measure of fiscal commitment risk and public credit risk evaluation indicators. Using China's provincial panel data from 2013 to 2019, we found that government credit risk reduces private partner participation. Private capital participates in PPP projects for profit if the local government has established good credit awareness and contractual spirit.

Research on the design and governance of new rural public environment based on regional culture

With the rapid development of new rural construction, new rural tourism has become an effective means to develop new rural economy. However, the current new rural planning is in the development stage, many ideas and ideas are not mature enough, and the concept of regional culture has not been widely accepted. Taking the new rural public environmental governance under regional culture as the research object, this paper summarizes some theories of new rural environmental governance based on the characteristics of regional culture through on-the-spot investigation, consulting a large number of literature and combined with various case studies. Firstly, taking the village form design and spatial layout design as the starting point, this paper introduces the new rural environment design method from the perspective of regional culture. Then, based on the full analysis of the current situation of public environment governance, this paper studies the governance of public environment in new rural areas based on the relevant knowledge of dynamic game theory. Through the analysis of the equilibrium solution of the game model, this paper explores the relevant countermeasures of rural governance and complete settlement of disputes.

Characterizing Agent Behavior in Revision Games with Uncertain Deadline

Revision game is a very recent advance in dynamic game theory and it can be used to analyze the trading in the pre-opening stock market. In such games, players prepare actions that will be implemented at a given deadline, before which they may have opportunities to revise actions. For the first time, we study the role of the deadline in revision games, which is the core component that distinguishes revision games from classic games. We introduce the deadline distribution into revision game model and characterize the sufficient and necessary condition for players’ strategies to constitute an equilibrium. The equilibrium strategy with respect to the deadline uncertainty is given by a simple differential equation set. Governed by this differential equation set, players initially fully cooperate, and the cooperation level decreases as time progresses. The uncertainty has a great impact on players’ behavior. As the uncertainty increases, players become more risk averse, in the sense that they prefer lower mutual cooperation rate rather than higher payoff with higher uncertainty. Specifically, they will not stay in full cooperation for a long time, while after they deviate from the full cooperation, they adjust their plans more slowly and cautiously. The deadline uncertainty can improve the competition and avoid collusion in games, which could be utilized for auction design and pre-opening stock market regulations.

Optimal trading mechanism for prosumer-centric local energy markets considering deviation assessment

Local energy markets with integrated distributed power prosumers who can produce and consume renewable energy are gradually becoming prosperous with the acceleration of the carbon neutrality process. It is crucial to explore optimal trading mechanism for prosumer-centric local energy markets considering deviation assessment due to the volatility of renewable energy. This study proposed a novel distributed power agency trading (DPAT) mechanism considering deviation assessment based on dynamic game theory, which is formulated by adopting a bilevel Stackelberg model whereby prosumers at lower levels optimize both electricity consumption and pricing strategies considering their expectations of the trading price. Specifically, when the purchase price offered by an agent is higher than the price the prosumer expected, the latter, as a buyer, will select the external market direct trading (EMDT) value. The subgame Nash equilibrium can be derived by nonlinear optimization theory, which demonstrates that prosumer equilibrium price equal to the agent, but equilibrium consumption strategies decrease linearly with aggregator and external market prices, where the former increases linearly with the latter. Furthermore, to explore prosumer’ mechanism selection preference at different times in the day when considering deviation assessment, this study conducted simulations based on actual data from the spot market. The results show that prosumers prefer the DPAT mechanism during peak load hours at noon and the EMDT mechanism during other periods of operation. Additionally, prosumers prefer the DPAT mechanism from the perspective of environmental benefits as it provides more than 8.8% carbon reduction compared to EMDT. This study can guide local energy market to establish optimal trading mechanisms and prosumers to develop optimal trading strategies, and promote achievement of regional carbon neutrality goals.

'Guidance' or 'Misleading'? The government subsidy and the choice of enterprise innovation strategy.

Government subsidies have a direct impact on firms' innovation strategies. The game relationship between the government, the subsidized firm and its competitors under different subsidy strategies affects firms' innovation behavior and thus innovation performance. This paper uses a dynamic evolutionary game theory approach based on cost-benefit differences to analyse the mechanisms by which government subsidy strategies affect firms' innovation strategies. It is found that the marginal benefits of a firm's innovation strategy will directly affect the game outcome, indicating that the choice of innovation strategy depends on the maximization of individual firm's interests. At the same time, a firm's innovation strategy is influenced by the firm's own innovation ability and competitors' innovation strategy, and there are two game equilibria. Government subsidies have a positive contribution to the innovation strategy choice of subsidized firms, but have a crowding-out effect on non-subsidized competing firms. The strength of the penalty (the efficiency of the implementation of government subsidies), the marginal revenue of the subsidized firms' rational use of government subsidies and the competitors' strategic choices will directly affect the game outcome.

Dynamic coordinated maintenance of wind-farms with risk-averse agents under CVaR criterion

We study a coordinated maintenance problem for multi-turbine offshore wind-farms. The deterioration of the turbines follows a Poisson process and the optimal order quantity for a single wind-farm, as well as for a coalition of wind-farms, is obtained using the analogy with the risk-averse newsvendor model considering the conditional value at risk (CVaR) criterion. We apply the theory of robust dynamic coalitional games to design a stable allocation mechanism that distributes the cost of the coalition among all the participants in a fair and stable way.

Modeling Goal Alignment in Human-AI Teaming: A Dynamic Game Theory Approach

As human-AI teaming becomes increasingly prevalent, goal alignment has emerged as a critical yet unsolved issue. Misaligned goals can be amplified by the situation and strategic interactions, which can further impact the teaming process and performance. These interrelated factors lack a systematic and computational model. To address this gap, we developed a dynamic game theoretical framework simulating the human-AI interdependency by integrating the Drift Diffusion Model simulating the goal alignment process. A 3 (Situation Structure) x 3 (Strategic Behaviors) x 2 (Initial Goal Alignment) simulation study of human-AI teaming was designed. Results showed that teaming with an altruistic agent in a competitive situation leads to the highest team performance. Moreover, goal alignment process can dissolve the initial goal conflict. Our study provides a first step of modeling goal alignment and implies a tradeoff between a balanced and cooperative team to guide human-AI teaming design.

Static and Dynamic Game Theory in Common Oil and Gas Fields: A Literature Review and Bibliometric Analysis

This paper provides a systematic literature review and analysis of game theory to model oil and gas scenarios. We select and review 2514 papers from Scopus, present a complex three-dimensional classification of the selected papers, and analyze the resultant citation network. According to the industry-based classification, the surveyed literature can be classified in common oil and gas supply chain fields. Based on the types of players, the literature can be classified into papers that use government-contractor games, the contractor–contractor games, contractor-subcontractor games, subcontractor–subcontractor games, or games involving other players. Based on the type of games used, papers using normal-form noncooperative games, normal-form cooperative games, extensive-form noncooperative games, or extensive-form cooperative games are present. Also, we show that each of the above classifications plays a role in influencing which papers are likely to cite a particular paper. However, the type-of-game classification exerts the strongest influence. Overall, the citation network in this field is sparse, implying that the authors' awareness of studies by other academics is suboptimal. Our review suggests that game theory is useful for modeling oil and gas scenarios. More work needs to be done on production in this domain and using extensive-form noncooperative games.

Free2Shard

In this paper, we formulate and study a new, but basic, distributed resource allocation problem arising in scaling blockchain performance. While distributed resource allocation is a well-studied problem in networking, the blockchain setting additionally requires the solution to be resilient to adversarial behavior from a fraction of nodes. Scaling blockchain performance is a basic research topic; a plethora of solutions (under the umbrella of sharding) have been proposed in recent years. Although the various sharding solutions share a common thread (they cryptographically stitch together multiple parallel chains), architectural differences lead to differing resource allocation problems. In this paper we make three main contributions: (a) we categorize the different sharding proposals under a common architectural framework, allowing for the emergence of a new, uniformly improved, uni-consensus sharding architecture. (b) We formulate and exactly solve a core resource allocation problem in the uni-consensus sharding architecture -- our solution, Free2shard, is adversary-resistant and achieves optimal throughput. The key technical contribution is a mathematical connection to the classical work of Blackwell approachability in dynamic game theory. (c) We implement the sharding architecture atop a full-stack blockchain in 3000 lines of code in Rust -- we achieve a throughput of more than 250,000 transactions per second with 6 shards, a vast improvement over state-of-the-art.

Pricing Strategy for Green Products Based on Disparities in Energy Consumption

The energy consumption disparity is an important factor affecting product pricing. The risk and the cost of new energy products are generally higher than those of traditional energy products, which results in conflicting pricing strategies between manufacturers and retailers. Applying the concepts from dynamic cooperative game theory, such as improved Shapley value, in this paper, we have studied the optimal pricing strategies of manufacturers and retailers in a cooperative and a noncooperative game. Based on policies and market conditions in China, we have used a logistic regression model to determine the impact of product sales, devised pricing strategies affected by the relevant government tax, and subsidy policy. The results show that, first, under the basic condition in which the manufacturer obtains profit, the optimal pricing of the retailer in a noncooperative game is more than that in a cooperative game. Second, the differential coefficient of the energy consumption of the two products in the cooperative game is greater than that in the noncooperative game. Third, the cooperative game not only plays an incentivizing role for retailers in setting reasonable prices of new energy products but also encourages manufacturers, producing a greater difference of energy consumption between traditional energy products and new energy products, which further reduces the consumption of new energy products. Finally, the strategies of sharing the green marketing costs by manufacturers and retailers can improve the total profits of the supply chain in addition to their own.

Using evolutionary game theory to study construction safety supervisory mechanism in China

PurposeIn China, external supervision on construction safety mainly comes from the government and supervision engineers (SEs). However, the construction safety supervisory mechanism (CSSM) contains some dilemmas affecting the improvement of safety performance, such as the declining impact of SEs, the increasing rent-seeking behaviors of contractor and excessive government interference. This study aims to depict and analyze the CSSM in China from an evolutionary game view. The objectives are to understand the supervision strategy and evolutionary behaviors of different stakeholders, propose suggestions for improving safety performance and help the key safety supervision stakeholders, especially the government, formulate a suitable safety supervision strategy.Design/methodology/approachThis research uses tripartite dynamic evolutionary game theory to study the CSSM in China and solve the stable equilibrium solution using system dynamics.FindingsThis study has revealed the game relationship of construction safety supervision mechanisms in China and solved the stable equilibrium solution. The results prove that a supervision engineer (SE) plays a crucial role in the CSSM, and “supervision engineer useless” is an unreasonable assertion. For government supervision agency (GSA), excessive inspection and free-market regulation are neither wise strategies. GSA can reduce the inspection frequency when general contractors (GCs) input high safety investments and SEs implement responsible supervision. But keeping proper government supervision to avoid GC's unlawful behaviors and SE's rent-seeking is indispensable. In addition, excessive governmental supervision will weaken SE's role, so the government should transfer some supervision powers to SE.Originality/valueThis study focuses on the dynamic evolution process between GSA, GC and SE. This method is different from most research that neglected the dynamic characteristic of system and game solution stability. The research methods not only contribute to construction safety supervision policy-making in China but also help to improve supervision efficiency in other countries and other fields.

Evolutionary Game Analysis of Co-Opetition Strategy in Energy Big Data Ecosystem under Government Intervention

This study discusses how to facilitate the barrier-free circulation of energy big data among multiple entities and how to balance the energy big data ecosystem under government supervision using dynamic game theory. First, we define the related concepts and summarize the recent studies and developments of energy big data. Second, evolutionary game theory is applied to examine the interaction mechanism of complex behaviors between power grid enterprises and third-party enterprises in the energy big data ecosystem, with and without the supervision of government. Finally, a sensitivity analysis is conducted on the main factors affecting co-opetition, such as the initial participation willingness, distribution of benefits, free-riding behavior, government funding, and punitive liquidated damages. The results show that both government supervision measures and the participants’ own will have an impact on the stable evolution of the energy big data ecosystem in the dynamic evolution process, and the effect of parameter changes on the evolution is more significant under the state of no government supervision. In addition, the effectiveness of the developed model in this work is verified by simulated analysis. The present model can provide an important reference for overall planning and efficient operation of the energy big data ecosystem.

Free2Shard

In this paper, we study a canonical distributed resource allocation problem arising in blockchains. While distributed resource allocation is a well-studied problem in networking, the blockchain setting additionally requires the solution to be resilient to adversarial behavior from a fraction of nodes. Scaling blockchain performance is a basic research topic; a plethora of solutions (under the umbrella of sharding ) have been proposed in recent years. Although the various sharding solutions share a common thread (they cryptographically stitch together multiple parallel chains), architectural differences lead to differing resource allocation problems. In this paper we make three main contributions: (a) we categorize the different sharding proposals under a common architectural framework, allowing for the emergence of a new, uniformly improved, uni-consensus sharding architecture. (b) We formulate and exactly solve a core resource allocation problem in the uni-consensus sharding architecture -- our solution, Free2shard, is adversary-resistant and achieves optimal throughput. The key technical contribution is a mathematical connection to the classical work of Blackwell approachability in dynamic game theory. (c) We implement the sharding architecture atop a full-stack blockchain in 3000 lines of code in Rust -- we achieve a throughput of more than 250,000 transactions per second with 6 shards, a vast improvement over state-of-the-art.

Multi-player dynamic game model for Bitcoin transaction bidding prediction

With the rapid rise of cryptocurrencies, it has become an urgent problem to realize the flat use of digital currency, with making it really put into use, and giving full play to its utility in the current economic market. This paper innovatively takes the maximization of user benefit as the key point to predict transaction bidding price combining dynamic game theory. The bidding price of user transaction not only refers to historical transactions, but also considers the impact on future subsequences, and the result describes the interaction between transactions in detail. Also this paper proposes a method to express user satisfaction and establishes a user benefit model accordingly, so as to ensure the transaction is packaged successfully to the greatest extent within the acceptable range of transaction pricing. Finally this paper compares the proposed model with conventional machine learning prediction algorithms, finding that when user does not participate in the trading for the first time, the prediction effect of this proposal is better than that of machine learning over small data sets, moreover superior to machine learning methods in prediction accuracy and sensitivity, with a lower time complexity.

On Durable-strategies Dynamic Game Theory

An empirically meaningful theory of dynamic games has to incorporate real-life phenomena. Durable strategies, which effects last for a period of time, are prevalent in real-life situations. Revenue generating investments, toxic waste disposal and purchase of durable goods are common examples of durable strategies. This paper first provides a review on durable-strategies dynamic game theory. A practically relevant advancement - random horizon durable-strategies dynamic games - yielding novel results in durable-strategies dynamic games theory is then presented. Dynamic optimization theorem, game formulations and HJB equations are derived. An illustrative example is provided. The theory and solution mechanism of durable-strategies cooperative dynamic games are also discussed.

Using chemical reaction network theory to show stability of distributional dynamics in game theory

<p style='text-indent:20px;'>This article shows how to apply results of chemical reaction network theory (CRNT) to prove uniqueness and stability of a positive equilibrium for pairs/groups distributional dynamics that arise in game theoretic models. Evolutionary game theory assumes that individuals accrue their fitness through interactions with other individuals. When there are two or more different strategies in the population, this theory assumes that pairs (groups) are formed instantaneously and randomly so that the corresponding pairs (groups) distribution is described by the Hardy–Weinberg (binomial) distribution. If interactions times are phenotype dependent the Hardy-Weinberg distribution does not apply. Even if it becomes impossible to calculate the pairs/groups distribution analytically we show that CRNT is a general tool that is very useful to prove not only existence of the equilibrium, but also its stability. In this article, we apply CRNT to pair formation model that arises in two player games (e.g., Hawk-Dove, Prisoner's Dilemma game), to group formation that arises, e.g., in Public Goods Game, and to distribution of a single population in patchy environments. We also show by generalizing the Battle of the Sexes game that the methodology does not always apply.</p>

Game Research on Risk Sharing of Rural Tourism Construction Projects

Rural tourism is an important starting point for industry to promote rural revitalization. After analyzing the risks that may be faced in the process of rural tourism construction projects, this paper introduces the dynamic game theory to establish a decision-making model for the optimal sharing ratio of shared risks in rural tourism PPP projects, and obtains the optimal Nash equilibrium solution of the model to determine the optimal ratio of risk sharing between the government and the tourism project contractor. The results show that in the dynamic game of risk sharing of rural tourism PPP projects with priority bidding by the government, the degree of information asymmetry, the loss coefficient of negotiation and the unequal status of the two parties will directly affect the optimal sharing ratio of risk sharing. Therefore, in the process of rural tourism construction, the government should publicize more information, and choose local enterprises. Construction enterprises also need to understand the relevant situation of the project from various aspects, so as to reduce information asymmetry.