Stable Coalition Research Articles

Null players, outside options, and stability: The conditional Shapley value

We suggest a new component efficient solution for monotonic TU games with a coalition structure, the conditional Shapley value. In contrast to other such solutions, it satisfies the null player property. Nevertheless, it accounts for the players’ outside options in productive components of coalition structures. For all monotonic games, there exist coalition structures that are stable under the conditional Shapley value. For voting games, such stable coalition structures support Gamson’s theory of coalition formation (Gamson, 1961).

Solidarity to achieve stability

Agents may form coalitions. Each coalition shares its endowment among its agents by applying a sharing rule. The sharing rule induces a coalition formation problem by assuming that agents rank coalitions according to the allocation they obtain in the corresponding sharing problem. We characterize the sharing rules that induce a class of stable coalition formation problems as those that satisfy a natural axiom that formalizes the principle of solidarity. Thus, solidarity becomes a sufficient condition to achieve stability.

A novel coalition game based distributed cooperative content caching in mobile edge networks

In mobile edge networks with mobile vehicles, road-side units (RSUs) can be used as edge nodes to cache some popular contents for moving vehicles in advance, and therefore improving the transmission efficiency and quality of user experience during vehicle-to-infrastructure (V2I) content communication. Transferring large files to a fast-moving car is a challenging task because of the limited communication time between the vehicle and the RSU. In this paper, we propose a cooperative content placement model for RSUs, in which multiple RSUs can jointly complete the cache and transmission of large files, so that the vehicle users can obtain the target content in the process of high-speed movement. To form cooperative coalitions between RSUs and place as much content as possible, a novel coalition game based distributed cooperative content caching scheme, namely CGD3C, is proposed, in which an RSU cooperative clustering algorithm and a resource balancing based coalition formation algorithm is proposed to merge and split the coalitions, so as to obtain a stable coalition structure. Finally, a cooperative content caching determination algorithm is proposed to determine the content placement with objective of maximizing the current interests. Our simulation results show that our proposed CGD3C can achieve stable and effective content delivery for high-speed moving vehicles, form an optimal RSU coalition structure independently, as well as improve the profit by 15%, the caching resource utilization by 24%, and the request hit rate by 12% on average in comparison with existing schemes.

Multi-objective distributed cooperative spectrum sensing for cognitive radio networks using greedy-based coalitional game

In this work, we propose a distributed cooperative spectrum sensing (CSS) scheme for cognitive radio networks applying a greedy-based coalitional game. We formulate the cooperative spectrum sensing problem as a multi-objective optimization problem using the weighted global criteria method. The objective of the formulated problem is to jointly consider the relative impacts of the three key performance metrics in CSS: throughput gain, penalty cost, and energy overhead. By integrating these three distinct metrics into a global optimization problem, we aimed to achieve a well-balanced trade-off, essential for deploying the CSS scheme across diverse network and application environments. We prove that the formulated CSS problem is non-deterministic polynomially hard (NP-hard). The computational complexity of the formulated CSS problem is decreased by proposing a heuristic scheme that produces a sub-optimal solution in polynomial time. We develop the heuristic scheme by putting forward a greedy-based coalitional game theoretic model. The proposed scheme exploits the spatial diversity of secondary users (SUs) in forming distributed coalitions to minimize the effects of attenuation and distortion on the transmitted signal. Further sensing energy overhead is reduced by dynamically deciding the sensing duration for the SUs based on their received signal strength. To establish the stability of the coalitional game model, we carry out proof which shows that the proposed heuristic algorithm converges to a stable coalition structure. Simulation-based results show the effectiveness of the proposed scheme in terms of average detection accuracy, utility, and energy overhead compared to conventional schemes.

SRM on the table: the role of geoengineering for the stability and effectiveness of climate coalitions

Geoengineering, including solar radiation management (SRM), has received increasing scrutiny due to the rise of climate extremes and slow progress in mitigating global carbon emissions. This climate policy option, even as a possibility, can have consequential implications for international climate governance. Here, we study how solar engineering affects the effectiveness and stability of a large set of regional coalitions through numerical simulations. We posit a requirement in terms of global political or economic power and analyze the exclusive membership coalition formation process when coalitions jointly decide on geoengineering and mitigation. We show that geoengineering can provide incentives for cooperation and partially solve the typical trade-off between stability and effectiveness of climate coalitions. However, temperature reduction mostly comes from deploying SRM within the coalition rather than from further emission reductions, thus exposing the world to relatively large-scale deployment of SRM with as of today uncertain potential side effects and risks.

A dynamic climate negotiation game achieving full cooperation

We present a repeated participation game where countries form a coalition for international environmental agreements over infinitely many periods. Countries may leave and re-enter coalitions. Payoff transfers are possible. In contrast to the literature on stable coalitions in a static model, we show that there exists a state-dependent subgame perfect equilibrium where the grand coalition forms in every period if countries are sufficiently patient. The grand coalition forms under countries' self-fulfilling belief that small coalitions will dissolve or enlarge to the grand coalition with an unfavorable transfer to non-participants. We further show that if coalitions are irreversible, the grand coalition gradually forms in finitely many periods in every Markov perfect equilibrium. The results are independent of a particular solution for the bargaining problem of coalition benefits.

How Do Local Party Systems Change after the Direct Election of Mayors? Analysis of the Institutional Reform in Lithuania

ABSTRACT The Lithuanian parliament in 2015 amended the electoral system of local elections by introducing direct election of mayors. The reform was intended to increase the accountability of mayors, to stabilize mayoral terms, and to encourage higher turnouts in local elections. We find that these aims were achieved partially. First, we observe reduced electoral fragmentation, increase in the vote shares of independent candidates, and a higher number of independent politicians elected to mayoral posts. Second, although the reelection rates of mayors increased, stability of local coalitions did not change much. Finally, the reform did not increase turnouts significantly.

Robin Hood to the Rescue: Sustainable Revenue‐Allocation Schemes for Data Cooperatives

The promise of consumer data along with advances in information technology has spurred innovation not only in the way firms conduct their business operations but also in the manner in which data are collected. A prominent institutional structure that has recently emerged is a data cooperative—an organization that collects data from its members, and processes and monetizes the pooled data. A characteristic of consumer data is the externality it generates: Data shared by an individual reveal information about other similar individuals; thus, the marginal value of pooled data increases in both the quantity and quality of the data. A key challenge faced by a data cooperative is the design of a revenue‐allocation scheme for sharing revenue with its members. An effective scheme generates a beneficial cycle: It incentivizes members to share high‐quality data, which in turn results in high‐quality pooled data—this increases the attractiveness of the data for buyers and hence the cooperative's revenue, ultimately resulting in improved compensation for the members. While the cooperative naturally wishes to maximize its total surplus, two other important desirable properties of an allocation scheme are individual rationality and coalitional stability. We first examine a natural proportional allocation scheme—which pays members based on their individual contribution—and show that it simultaneously achieves individual rationality, the first‐best outcome, and coalitional stability, when members' privacy costs are homogeneous. Under heterogeneity in privacy costs, we analyze a novel hybrid allocation scheme and show that it achieves both individual rationality and the first‐best outcome, but may not satisfy coalitional stability. Finally, our RobinHood allocation scheme—which uses a fraction of the revenue to ensure coalitional stability and allocates the remaining based on the hybrid scheme—achieves all the desirable properties.

Group Formation and the Evolution of Human Social Organization

Humans operate in groups that are oftentimes nested in multilayered collectives such as work units within departments and companies, neighborhoods within cities, and regions within nation states. With psychological science mostly focusing on proximate reasons for individuals to join existing groups and how existing groups function, we still poorly understand why groups form ex nihilo, how groups evolve into complex multilayered social structures, and what explains fission–fusion dynamics. Here we address group formation and the evolution of social organization at both the proximate and ultimate level of analysis. Building on models of fitness interdependence and cooperation, we propose that socioecologies can create positive interdependencies among strangers and pave the way for the formation of stable coalitions and groups through reciprocity and reputation-based partner selection. Such groups are marked by in-group bounded, parochial cooperation together with an array of social institutions for managing the commons, allowing groups to scale in size and complexity while avoiding the breakdown of cooperation. Our analysis reveals how distinct group cultures can endogenously emerge from reciprocal cooperation, shows that social identification and group commitment are likely consequences rather than causes of group cooperation, and explains when intergroup relations gravitate toward peaceful coexistence, integration, or conflict.

France: Political Developments and Data for 2022

AbstractAs an election year for President Macron and his majority, 2022 proved itself a challenge. President Macron did win his run‐off against Le Pen, once again, but the key result of the legislative elections was the formation of a minority government. LREM (La République En Marche!), relabeled since as Revival, did not secure a majority in the National Assembly and was unable to form a stable coalition with any significant partner in the context of continuing polarization of the party system. The year 2022 brought unexpected developments on the left, with a new coalition called Nupes (New Popular Green and Social Union, Nouvelle Union Populaire Ecologique et Sociale) and bringing together all major left‐wing parties under the leadership of Mélenchon and LFI (La France Insoumise). Meanwhile, the two formerly dominant parties since the 1980s, the Socialist Party and the Republicans, have almost vanished from the scene.

Coalition Game of Radar Network for Multitarget Tracking via Model-Based Multiagent Reinforcement Learning

Task assignment is crucial for multitarget tracking of the radar network and is mainly solved by centralized optimization methods, which results in the issues of robustness deficiency, high computational cost, and inflexible adaptability in complex environments. To overcome these issues, task assignment of the radar network for multitarget tracking is formulated as a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiagent decision-making and learning</i> problem, where each radar node in the network acts as an intelligent agent that can make the tracking decision according to its task preference and interact with other agents for the sake of the best network utility. To describe the decision references of radar nodes for various tasks, the criterion for the design of the utility function is presented, and a utility function under this criterion is devised based on the quality of service framework. Then, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">coalition game with transferrable utility</i> is developed for task assignment, where the utility of the coalition is completely transferred to all coalition members. The existence of the stable coalition partition of the developed game is analyzed theoretically, and the model-based multiagent <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">random Fourier features reinforcement learning</i> (RFFRL) algorithm is proposed to solve the optimal solution to the game in the high dimensional state space, which is proven to be converged at a Nash-stable coalition partition. Some numerical simulation results are provided to illustrate the effectiveness of the proposed algorithm in terms of tracking performance and resource conservation.

Coalition formation problems with externalities

We study coalition formation problems with externalities. We prove that, if expectations are not prudent a stable coalitions structure may fail to exist. Under prudent expectations a stable and efficient coalition structure exists if the set of admissible coalitions is single-lapping. However, under this assumption the stable set is not a singleton, and no stable strategy-proof revelation mechanism exists, differently from the case without externalities. Finally, the stable correspondence is Nash implementable.

Tri-level stochastic transactive energy management and improved profit distribution scheme for multi-vectored networked microgrids: A multi-objective framework

To ensure the optimal co-operation of multi-vectored network microgrids (MV-NMG), this paper focuses on cooperation-based transactive energy management. Transactive energy management facilitates microgrids to share their green resources to form a sustainable coalition. To ensure the coalition's stability, the gained profit should be allocated among the participants impartially. Thus, this paper proposes a tri-level energy management framework, including an improved payoff allocation scheme for the MV-NMG system to ensure coalition and microgrids' collective and individual interests, respectively. At the first level, the stochasticity of renewables is quantified. Then, a two-stage, multi-objective problem formulation is developed at the second level to address the coalition's collective objectives. Hence, four MV-MGs are modeled with a demand response and advanced energy storage units. Further, a free, peer-to-peer community market is developed, which ensure zero green energy spillage. Results demonstrate that the proposed scheme allows the coalition to achieve its collective interests by reducing the operating cost by 30.1 % and GHG emissions by 22.1 % while improving the network's self - reliability by 21.3 %. Finally, at the third level, the proposed new payoff allocation mechanism rewards and penalizes the microgrids based on their special attributes and ensures the individual interests of MV-MGs.

Overlapping communities detection through weighted graph community games.

We propose a new model to detect the overlapping communities of a network that is based on cooperative games and mathematical programming. More specifically, communities are defined as stable coalitions of a weighted graph community game and they are revealed as the optimal solution of a mixed-integer linear programming problem. Exact optimal solutions are obtained for small and medium sized instances and it is shown that they provide useful information about the network structure, improving on previous contributions. Next, a heuristic algorithm is developed to solve the largest instances and used to compare two variations of the objective function.

Reaching Individually Stable Coalition Structures

The formal study of coalition formation in multi-agent systems is typically realized in the framework of hedonic games, which originate from economic theory. The main focus of this branch of research has been on the existence and the computational complexity of deciding the existence of coalition structures that satisfy various stability criteria. The actual process of forming coalitions based on individual behavior has received little attention. In this article, we study the convergence of simple dynamics leading to stable partitions in a variety of established classes of hedonic games, including anonymous, dichotomous, fractional, and hedonic diversity games. The dynamics we consider is based on individual stability: an agent will join another coalition if she is better off and no member of the welcoming coalition is worse off. Our results are threefold. First, we identify conditions for the (fast) convergence of our dynamics. To this end, we develop new techniques based on the simultaneous usage of multiple intertwined potential functions and establish a reduction uncovering a close relationship between anonymous hedonic games and hedonic diversity games. Second, we provide elaborate counterexamples determining tight boundaries for the existence of individually stable partitions. Third, we study the computational complexity of problems related to the coalition formation dynamics. In particular, we settle open problems suggested by Bogomolnaia and Jackson, Brandl et al., and Boehmer and Elkind.

An incentive mechanism for integration of business applications between organizations

Extending services and operations of organizations in the field of e-business or e-government sometimes requires the integration of business applications. However, sometimes due to challenges and risks, such as complex business processes reengineering, upstream organizations are reluctant to integrate their applications. This paper focuses on two critical questions; (1) How can organizations be encouraged to participate in integrating their business applications? (2) What is the amount of incentives required? In this study, cooperative game theory and the externalities of these systems have been considered to form a stable coalition between organizations for integrating their business applications. We provided an algorithm for determining the incentives to integrate the business applications with other organizations in this coalition. These incentives can be extended to various management issues for better decision-making such as economic aspects, public subsidies, and public participation. The results of experiments have shown that creating a coalition based on this strategy is always possible, and the benefits of organizations in the coalition rise with increasing service delivery in business applications.

Pricing, coalition stability, and profit allocation in the pull assembly supply chains under competition

Pricing, coalition stability, and profit allocation in the pull assembly supply chains under competition

The problem of financing global public goods

A longstanding result from decades of research on the provision of global public goods, is that stable coalitions of cooperating countries are small when the benefits to cooperating are large. This “paradox” of cooperation is seemingly overcome in a recent paper “The Strategic Dimension of Financing Global Public Goods”, by Kornek and Edenhofer (2020). The authors propose a global-public goods game in which countries finance a compensation fund that can balance abatement costs among members. The fund is based on financial transfers, and in the often-explored case of linear benefits and quadratic costs, the proposed institution is credited as being able to support a stable grand coalition. However, when looking carefully at the model, the promising result relies on assumptions and features of an international institution that are not credible because they restrict members’ rights to opt out. The institution’s success relies on countries being required to transfer funds in response to below-average abatement levels. In this short paper we show that when countries have the outside option to renege on the terms of the agreement, no money would be transferred and the institution proposed by Kornek and Edenhofer (2020) reverts to the non-cooperative outcome.

Editorial Introduction: Contributing to the policy process literatures

Editorial Introduction: Contributing to the policy process literatures

Cooperative game based two-stage consensus adjustment mechanism for large-scale group decision making

Large-scale group decision making (LSGDM) is a powerful technology to deal with complex decision problems. As decision makers (DMs) in LSGDM come from different fields with various backgrounds and expertise, their perception of the same decision problem is largely divergent. The measure and improvement of consensus can obtain widely accepted decision results. In this process, the behaviors of DMs are interactive. The amount and direction of adjustments influence not only their consensus level but also that of other DMs. Therefore, the fairness and rationality of the consensus adjustment mechanism are fundamental. Considering the characteristics of LSGDM, this paper introduces two-stage consensus adjustment mechanisms from the perspective of cooperative game theory. In the first stage, players are DMs within each subgroup, and subgroups are regarded as players in the second stage. Further, the coalition payoffs are defined as the minimum consensus adjustment determined by the built models. To show the designated consensus adjustment cooperative games are essential, we prove that they are supper-additive. Considering the marginal contribution of DMs to consensus adjustment, a two-stage Shapley consensus adjustment mechanism is offered. Namely, the Shapley function is adopted to allocate the consensus adjustment to DMs and subgroups. When the Shapley consensus adjustment does not satisfy coalitional stability, a two-stage core-Nash bargaining consensus adjustment mechanism is provided, which can overcome the drawback of the two-stage Shapley consensus adjustment mechanism. Moreover, two new algorithms for LSGDM are proposed. Finally, a numerical example is provided to show the feasibility of the new method, and a comparison analysis is made.