Game-theoretic Perspective Research Articles

Mitigating the Rashomon Effect in Counterfactual Explanation: A Game-theoretic Approach

Counterfactual examples (CEs) are generally created to interpret the decision of a model. In this case, if a model makes a certain decision for an instance, the CEs of that instance reverse the decision of the model. There are many advantages of using counterfactuals as a way of explaining model decisions; however, there is one issue known as the Rashomon Effect that might dissuade target/intended users from using counterfactuals. If someone is presented with too many options, this might be overwhelming to them, and they might end up choosing an option that is not optimal or ideal for them. In this case, the Rashomon Effect is an impediment to realizing the full potential of counterfactual explanations. To utilize the full power of CEs and make them more helpful, we need to address the Rashomon Effect. In this work, we focus on this issue from game-theoretic perspectives to help target users make informed and feasible decisions by finding highly suitable CEs. In this case, finding good counterfactuals will be a game between two players where each of them tries to find better CEs.

Diversity in valuing social contact and risk tolerance leading to the emergence of homophily in populations facing infectious threats.

How self-organization leads to the emergence of structure in social populations remains a fascinating and open question in the study of complex systems. One frequently observed structure that emerges again and again across systems is that of self-similar community, i.e., homophily. We use a game theoretic perspective to explore a case in which individuals choose affiliation partnerships based on only two factors: the value they place on having social contacts, and their risk tolerance for exposure to threat derived from social contact (e.g., infectious disease, threatening ideas, etc.). We show how diversity along just these two influences is sufficient to cause the emergence of self-organizing homophily in the population. We further consider a case in which extrinsic social factors influence the desire to maintain particular social ties, and show the robustness of emergent homophilic patterns to these additional influences. These results demonstrate how observable population-level homophily may arise out of individual behaviors that balance the value of social contacts against the potential risks associated with those contacts. We present and discuss these results in the context of outbreaks of infectious disease in human populations. Complementing the standard narrative about how social division alters epidemiological risk, we here show how epidemiological risk may deepen social divisions in human populations.

A Differential Privacy Approach to Preserve GWAS Data Sharing based on A Game Theoretic Perspective

A Differential Privacy Approach to Preserve GWAS Data Sharing based on A Game Theoretic Perspective

Self-organized Partition of Distribution Networks with Distributed Generations and Soft Open Points

Islanding operation relying on distributed generations (DGs) is anticipated to be a promising operational measure for resilience enhancement of distribution networks. In this paper, a self-organized network partition framework for controllable DGs (CDGs) is proposed for the distribution network with DGs and soft open points (SOPs) from a game-theoretic perspective. The labeled numbers of the nodes on paths between every two adjacent CDGs are used as the optimization variables in the partition formation, which can avoid a large number of invalid partition schemes. Two objectives including the weighted recovered load and the power loss are considered, which reflect the goals of maximizing the critical load recovery and minimizing the power loss, respectively. The power loss is determined through the AC power flow calculation using Newton-Raphson method considering the operational characteristics of SOPs. The partition problem is modeled as a discrete bi-objective game, which is further transformed into a continuous game model, and the existence of the Pareto-Nash equilibrium is also proved. A decentralized method is developed to solve the proposed bi-objective game relying on the local communications and a global information discovery scheme, which is more practical after the extreme events. Numerical studies on the IEEE 69-bus distribution system and a 135-bus multi-feeder system are performed to validate the effectiveness of the proposed method. The proposed model is applied in different network topologies, and compared with the centralized optimization models. The robustness of the method to communication failures is analyzed, and the scalability of the proposed model is also validated through testing it in a larger distribution network.

A game-theoretic perspective to study a nonlinear stochastic parabolic model of population competition

In this paper, a game of competition between two populations is designed. Populations are considered as two players competing against each other to increase their sizes. Players have been provided with costly two-component strategies. Population densities are described by two coupled nonlinear stochastic second-order parabolic equations. We have added stochastic terms to the deterministic model to consider random perturbations. First, we have considered the stochastic payoff functions and proved the game has a unique stochastic Nash equilibrium. Then, we have shown the stochastic Nash equilibrium is also a Nash equilibrium for the game with deterministic payoff functions defined by expectation. Cooperative game is also studied and stochastic Pareto efficient strategies are obtained. Then, the existence and uniqueness analyses of the deterministic Nash equilibrium and deterministic Pareto efficient strategies for the game with deterministic payoff functions are provided. The explicit forms of Nash equilibriums and Pareto efficient strategies are presented. Results about the losses the players experience when they don't cooperate are given. Finally, some numerical experiments are included to illustrate what we have claimed in the statements of theorems and show the effects of the Nash equilibrium and Pareto efficient strategy on the payoffs of the players.

Games researchers play: conceptual advancement versus validation strategies

Conceptual advances and validation are critical to research, yet at odds. Using a game theoretical perspective, we show that a mixed strategy combining advances and validation, leads to increases in both individual researchers' and societal gains. This win-win outcome can be used to design new research strategies, funding, and recognition standards.

Disparity in socio-economic status explains the pattern of self-medication of antibiotics in India: understanding from game-theoretic perspective.

The emergence of antimicrobial resistance has raised great concern for public health in many lower-income countries including India. Socio-economic determinants like poverty, health expenditure and awareness accelerate this emergence by influencing individuals' attitudes and healthcare practices such as self-medication. This self-medication practice is highly prevalent in many countries, where antibiotics are available without prescriptions. Thus, complex dynamics of drug- resistance driven by economy, human behaviour, and disease epidemiology poses a serious threat to the community, which has been less emphasized in prior studies. Here, we formulate a game-theoretic model of human choices in self-medication integrating economic growth and disease transmission processes. We show that this adaptive behaviour emerges spontaneously in the population through a self-reinforcing process and continual feedback from the economy, resulting in the emergence of resistance as externalities of human choice under resource constraints situations. We identify that the disparity between social-optimum and individual interest in self-medication is primarily driven by the effectiveness of treatment, health awareness and public health interventions. Frequent multiple-peaks of resistant strains are also observed when individuals imitate others more readily and self-medication is more likely. Our model exemplifies that timely public health intervention for financial risk protection, and antibiotic stewardship policies can improve the epidemiological situation and prevent economic collapse.

Arboricity games: the core and the nucleolus

The arboricity of a graph is the minimum number of forests required to cover all its edges. In this paper, we examine arboricity from a game-theoretic perspective and investigate cost-sharing in the minimum forest cover problem. We introduce the arboricity game as a cooperative cost game defined on a graph. The players are edges, and the cost of each coalition is the arboricity of the subgraph induced by the coalition. We study properties of the core and propose an efficient algorithm for computing the nucleolus when the core is not empty. In order to compute the nucleolus in the core, we introduce the prime partition which is built on the densest subgraph lattice. The prime partition decomposes the edge set of a graph into a partially ordered set defined from minimal densest minors and their invariant precedence relation. Moreover, edges from the same partition always have the same value in a core allocation. Consequently, when the core is not empty, the prime partition significantly reduces the number of variables and constraints required in the linear programs of Maschler’s scheme and allows us to compute the nucleolus in polynomial time. Besides, the prime partition provides a graph decomposition analogous to the celebrated core decomposition and the density-friendly decomposition, which may be of independent interest.

On the Price of Anarchy for Flows over Time

Dynamic network flows, or network flows over time, constitute an important model for real-world situations in which steady states are unusual, such as urban traffic and the internet. These applications immediately raise the issue of analyzing dynamic network flows from a game-theoretic perspective. In this paper, we study dynamic equilibria in the deterministic fluid queuing model in single-source, single-sink networks—arguably the most basic model for flows over time. In the last decade, we have witnessed significant developments in the theoretical understanding of the model. However, several fundamental questions remain open. One of the most prominent ones concerns the price of anarchy, measured as the worst-case ratio between the minimum time required to route a given amount of flow from the source to the sink and the time a dynamic equilibrium takes to perform the same task. Our main result states that, if we could reduce the inflow of the network in a dynamic equilibrium, then the price of anarchy is bounded by a factor, parameterized by the longest path length that converges to [Formula: see text], and this is tight. This significantly extends a result by Bhaskar et al. (SODA 2011). Furthermore, our methods allow us to determine that the price of anarchy in parallel-link and parallel-path networks is exactly 4/3. Finally, we argue that, if a certain, very natural, monotonicity conjecture holds, the price of anarchy in the general case is exactly [Formula: see text].

Load Balancing for Distributed Intelligent Edge Computing: A State-Based Game Approach

The introduction of artificial intelligence (AI) into edge computing could significantly improve its quality of service. Connecting them into a system can provide services for a wider range. However, due to the mobility of the crowd and mobile devices, the load imbalance issue of these interconnected intelligent edge servers (IESs) will cause severe impacts on their service performance. To this end, we investigate load balancing for the distributed IESs from the game theoretic perspective and propose a state-based distributed learning algorithm. Firstly, by modelling the IES cost as the deviation between its execution time and the system average execution time, we formulate load balancing as a state-based game where each IES competes to maximize its own utility. Secondly, according to the definition of the recurrent state Nash equilibrium, we prove that this game has such an equilibrium by establishing a potential function at each reachable state. Finally, we propose a state-based distributed learning algorithm to obtain the pure Nash equilibrium strategy of each IES. Then, an ordinary differential equation is derived to prove the convergence of the algorithm. In comparison with existing works, our approach could largely improve load balancing for the distributed IESs and thus enhance their service performance.

Customer Behavior Analysis in Ticket Windows at Scenic Spots from Game-Theoretic Perspective

In service industries, especially in some ticket windows at scenic spots, affected by congestion, some customers often find excuses or ask the acquaintances in the queue so as to jump the queue and complete their corresponding service as early as possible. In this paper, we model the queueing phenomenon in the ticket windows at scenic spots as a special queue, namely, the so-called “team queue.” Although this phenomenon often happens in daily life, it is less well known to people. In a team queue, an arriving customer first searches the queue from the top to bottom to see if some of his teammates are already in the queue. If yes, he would join the queue and be served with his teammates; otherwise, he would join the queue at the tail. To this end, arising from the customers’ perspective, the strategic behavior of queueing customers in the ticket windows at scenic spots is analyzed. On the basis of considering the waiting cost and reward, the individual strategies and social optimal strategies of queueing customers are derived, regarding the joining or balking dilemma and for the observable and unobservable cases. Finally, to demonstrate how various parameters affect the joining strategies, some numerical examples are provided.

Algorithms for flows over time with scheduling costs

Flows over time have received substantial attention from both an optimization and (more recently) a game-theoretic perspective. In this model, each arc has an associated delay for traversing the arc, and a bound on the rate of flow entering the arc; flows are time-varying. We consider a setting which is very standard within the transportation economic literature, but has received little attention from an algorithmic perspective. The flow consists of users who are able to choose their route but also their departure time, and who desire to arrive at their destination at a particular time, incurring a scheduling cost if they arrive earlier or later. The total cost of a user is then a combination of the time they spend commuting, and the scheduling cost they incur. We present a combinatorial algorithm for the natural optimization problem, that of minimizing the average total cost of all users (i.e., maximizing the social welfare). Based on this, we also show how to set tolls so that this optimal flow is induced as an equilibrium of the underlying game.

Space Exploration Architecture and Design Framework for Commercialization

The trend of space commercialization is changing the decision-making process for future space exploration architectures, and there is a growing need for a new decision-making framework that explicitly considers the interactions between the mission coordinator (i.e., government) and the commercial players. In response to this challenge, this paper develops a framework for space exploration and logistics decision making that considers the incentive mechanism to stimulate commercial participation in future space infrastructure development and deployment. By extending the state-of-the-art space logistics design formulations from the game-theoretic perspective, the relationship between the mission coordinator and commercial players is first analyzed, and then the formulation for the optimal architecture design and incentive mechanism in three different scenarios is derived. To demonstrate and evaluate the effectiveness of the proposed framework, a case study on lunar habitat infrastructure design and deployment is conducted. Results show how total mission demands and in-situ resource utilization system performances after deployment may impact the cooperation among stakeholders. As an outcome of this study, an incentive-based decision-making framework that can benefit both the mission coordinator and the commercial players from commercialization is derived, leading to a mutually beneficial space exploration between the government and the industry.

Food supply chain coordination for growing items: A trade-off between market coverage and cost-efficiency

The accurate operation of a Food Supply Chain (FSC) is a critical issue as it directly interfaces with health and safety matters. This study addresses coordination and conflict management in a three-level FSC that embraces a new inventory type known as growing items like poultry and livestock. The chain involves a rearing farm as the supplier, a processed food producer as the manufacturer, and multiple processed food retailers. Vendor Managed Inventory (VMI) is applied by the manufacturer to handle the retailers' systems and prevent replenishment mismatches and thereby food waste. To increase its market coverage, the manufacturer needs to provide the retailers with enough incentives to enter this setting. So, a cost-sharing contract is designed under which the manufacturer undertakes a fraction of the retailers’ holding costs. Accordingly, the manufacturer faces two contradictory targets, increasing its market coverage by convincing the retailers to enter the system on the one hand and managing its costs efficiently on the other hand. An analytic solution approach with a game-theoretic perspective is developed to solve the model. Extensive numerical experiments and a case study are provided, presenting fruitful managerial insights that can be utilized by the policymakers and chain members under different settings. The results highlight the efficiency of our VMI and cost-sharing collaboration scheme in enhancing the performance of the chain.

Switching defence for switched systems under malicious attacks: A Stackelberg game approach

The security issue of switched systems is researched from a noncooperative dynamic game-theoretic perspective in this paper. A Stackelberg game is developed for the switched autonomous system suffering malicious attacks, and the Stackelberg equilibrium switching and attack strategies are constructed respectively. Afterwards, the proposed game-theoretic approach is extended to switched control systems. A Stackelberg Nash game is consequently established to characterize the hierarchical decision making processes, where the controller and the attacker are the followers who simultaneously make their own decisions, and a sufficient condition is provided for the construction of the Stackelberg Nash equilibrium. Finally, a continuous stirred tank reactor is exploited to validate the effectiveness and applicability of the proposed results.

Optimal pricing for ferry services with a new entrant: a game-theoretic perspective

This paper investigates the pricing model between an incumbent ferry firm and a new-entrant sea bus firm. First, we study the influences of sea buses entering the ferry market. Next, based on the differences in power structures, we analyze the impact of weather on both companies’ operations in Bertrand and two Stackelberg models, and we consider a case in which both firms belong to the same parent firm. Finally, we study the strategies adopted by the ferry firm to protect its market share against the invasion of sea buses. We find that the sea bus firm’s entrance into the ferry market will increase the number of passengers taking ferries. Both companies’ profits are greater in the two Stackelberg models than in the Bertrand model. The two companies’ profits in the Stackelberg models partially rely on the weather. Finally, vicious price competition will lead to losses on both sides.

A game theoretic perspective on the management of shared North Sea fishery resources: Pre and post Brexit

Since the introduction of the 200 nautical mile Exclusive Economic Zone (EEZ) regime, North Sea coastal states have cooperated in the management of shared stocks. Norway and the EU have jointly managed six shared stocks through the 1980 Agreement which includes the annual setting of total allowable catch quotas (TACs), quota shares and access agreements. This article first attempts to explain in a game theoretic context why cooperative management of shared North Sea fish stocks has been stable for more than 40 years. Brexit represented a shock to the cooperative agreement, and there are now three parties to the negotiations. The UK EEZ is important not only for British fishermen, but also for Norway and the EU27. The UK and the EU have agreed on a Trade and Cooperation Agreement which includes fisheries, but Norway and the UK have not yet reached a fisheries agreement. In the second part of the article we analyse the UK-EU fisheries agreement, the continuation of the 1980 Agreement, and the future fisheries relationship between the UK and Norway.

China Special Issue B Introduction: Cultural Distance, Households, Innovation, and Cultural Industry

Special Issue B continues to address a set of research questions to complement Special Issue A which focused on China’s rapid economic growth and the associated challenges. Examples discussed include unbalanced domestic growth, Africa-China migration, a game theoretic perspective on cooperation, and industry structure and policy changes. Critically, Issue B identifies opportunities as well as uncertainties for Chinese enterprises and institutions in their quest to become the world’s leading economy. Specifically, papers examine issues related to the China Multinational Corporations (CMNC), workforce mobility, technological innovation, and the economic development of cultural industry, specifically, the film industry, all of which are having a profound impact on China’s economic landscape. Their research focus includes: CMNC sociocultural distance and its impact on cross-border replication of activities; socio-political decisions in relation to innovation efficiency; the ‘middle-income trap’ and its effect on workforce mobility and ‘functional inequality’. The frameworks, models, and theories discussed in these papers should help scholars to gain a better understanding of some of the social determinants of economic decisions as they relate to China’s economic development.

Selfish Creation of Social Networks

Understanding real-world networks is a core research endeavor within the last two decades. Network Creation Games are a promising approach for this from a game-theoretic perspective. In these games, selfish agents corresponding to nodes in a network strategically decide which links to form to optimize their centrality. Many versions have been introduced and analyzed, but none of them fits to modeling the evolution of social networks. In real-world social networks connections are often established by recommendations from common acquaintances or by a chain of such recommendations. Thus establishing and maintaining a contact with a friend of a friend is easier than connecting to complete strangers. This explains the high clustering, i.e., the abundance of triangles, in real-world social networks. We propose and analyze a network creation model inspired by real-world social networks. In our model edges are formed via bilateral consent of both endpoints and the cost for establishing and maintaining an edge is proportional to the distance of the endpoints before establishing the connection. We provide results for generic cost functions which essentially only must be convex functions in the distance of the endpoints without the respective edge. For this broad class of cost functions we provide many structural properties of equilibrium networks and prove (almost) tight bounds on the diameter, the Price of Anarchy and the Price of Stability. Moreover, as a proof-of-concept we show via experiments that the created equilibrium networks of our model indeed closely mimic real-world social networks. We observe degree distributions that seem to follow a power-law, high clustering, and low diameters. This can be seen as a promising first step towards game-theoretic network creation models that predict networks featuring all core real-world properties.

Competitive Intelligence and Strategy Formulation: an Evaluation from the Game Theoretical Perspective

Bu çalışmada işletme stratejilerinin oluşturulmasında, oyun teorisinin rekabet istihbaratı sürecine sağlayabileceği katkıların ortaya çıkarılması amaçlanmıştır. Bu amaçla, öncelikle oyun teorisi ve rekabet istihbaratı arasındaki kavramsal bağlantılar açığa çıkarılmış ve ardından statik ve dinamik oyunlarda temel strateji analizleri ve denge kavramları tanıtılmıştır. Rekabet istihbaratı sürecinin bir parçası olarak strateji analizlerinde, karar alıcılarca dikkate alınabilecek farklı bakış açılarına ilişkin çıkarımlar yapılmıştır. Oyun teorisi, karar alıcılara, rekabetçi yapılar içerisinde işbirliği fırsatlarını yakalayabilmeleri ve kazançlarını artırabilmeleri için daha fazla değer yaratan oyunları keşfetmeye imkân vermektedir. Rakip işletmeler açısından işbirliğinin uzun dönemli kazançlarının, rekabetin kısa dönemli yüksek kazançlarına tercih edilebileceği gösterilmiştir. Ayrıca, rakip stratejilerin kredibilitesine ilişkin ölçütlerle makul olmayan stratejilerin nasıl tespit edildiği ve ilk hareket edenin avantajının nasıl ortaya çıktığı teorik olarak gösterilmiştir. Oyun teorisi, analiz araçları ve modelleme altyapısıyla, rekabet istihbaratının hedeflerine önemli ölçüde katkı sağlayabilecek bir araçtır. Bu çalışma, rekabet istihbaratı perspektifinden oyun teorisinin strateji oluşturmadaki rolüne değinerek rekabet istihbaratı literatürüne katkı sağlamaktadır.