Set Of Coalitions Research Articles

What citizens think about minority governments in majority coalition settings

What citizens think about minority governments in majority coalition settings

A decentralized control approach in hypergraph distributed optimization decomposition cases

We study the main decomposition approaches (primal, dual and primal–dual) for a distributed optimization problem from a dynamical system perspective where the couplings among the variables of the optimization problem are described by an undirected, unweighted hypergraph. We conduct stability analysis for the respective dynamical systems of the decomposition cases by using non linear decentralized control theoretic techniques and spectral properties of the respective communication matrices, i.e., the incidence and the Laplacian matrices of the hypergraph. Finally, we provide numerical simulations under a specific coalitional setting that demonstrate the superiority of the hypergraph compared to its respective graph analogue, the clique expansion graph, for the given decomposition algorithms in terms of convergence rate and information transmission efficiency.

Strength in coalitions: Community detection through argument similarity

We present a novel argumentation-based method for finding and analyzing communities in social media on the Web, where a community is regarded as a set of supported opinions that might be in conflict. Based on their stance, we identify argumentative coalitions to define them; then, we apply a similarity-based evaluation method over the set of arguments in the coalition to determine the level of cohesion inherent to each community, classifying them appropriately. Introducing conflict points and attacks between coalitions based on argumentative (dis)similarities to model the interaction between communities leads to considering a meta-argumentation framework where the set of coalitions plays the role of the set of arguments and where the attack relation between the coalitions is assigned a particular strength which is inherited from the arguments belonging to the coalition. Various semantics are introduced to consider attacks’ strength to particularize the effect of the new perspective. Finally, we analyze a case study where all the elements of the formal construction of the formalism are exercised.

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.

Robust equilibria in tournaments

We study robust equilibria in tournaments, where agents endowed with power form coalitions, and the coalition formed with the highest power prevails. We introduce the No-Threat Equilibrium (NTE), a stable partition where if a coalition deviates, then a new coalition could counter by forming an even stronger coalition. The NTE exists for any power function and preferences if and only if the set of feasible coalitions is a ‘Helly’ family.In contrast, the core is a partition in which no group of agents can profitably deviate by forming a feasible coalition, assuming that other agents do not react to such a deviation. The core is not empty for any power function and preferences if and only if the set of feasible coalitions has a ‘hierarchical-structure’.The paper also adapts and characterizes other stability concepts to tournaments, including the α-core, β-core, farsighted core and bargaining set.

Coalition-based task assignment with priority-aware fairness in spatial crowdsourcing

With the widespread use of networked and geo-positioned mobile devices, e.g., smartphones, Spatial Crowdsourcing (SC), which refers to the assignment of location-based tasks to moving workers, is drawing increasing attention. One of the critical issues in SC is task assignment that allocates tasks to appropriate workers. We propose and study a novel SC problem, namely Coalition-based Task Assignment (CTA), where the spatial tasks (e.g., home improvement and furniture installation) may require more than one worker (forming a coalition) to cooperate to maximize the overall rewards of workers. We design a greedy and an equilibrium-based CTA approach. The greedy approach forms a set of worker coalitions greedily for performing tasks and uses an acceptance probability to identify high-value task assignments. In the equilibrium-based approach, workers form coalitions in sequence and update their strategies (i.e., selecting a best-response task), to maximize their own utility (i.e., the reward of the coalition they belong to) until a Nash equilibrium is reached. Since the equilibrium obtained is not unique and optimal in terms of total rewards, we further propose a simulated annealing scheme to find a better Nash equilibrium. To achieve fair task assignments, we optimize the framework to distribute rewards fairly among workers in a coalition based on their marginal contributions and give workers who arrive first at the SC platform highest priority. Extensive experiments demonstrate the efficiency and effectiveness of the proposed methods on real and synthetic data.

A Core-Partition Ranking Solution to Coalitional Ranking Problems

A coalitional ranking problem is described by a weak order on the set of nonempty coalitions of a given agent set. A social ranking is a weak order on the set of agents. We consider social rankings that are consistent with stable/core partitions. A partition is stable if there is no coalition better ranked in the coalitional ranking than the rank of the cell of each of its members in the partition. The core-partition social ranking solution assigns to each coalitional ranking problem the set of social rankings such that there is a core-partition satisfying the following condition: a first agent gets a higher rank than a second agent if and only if the cell to which the first agent belongs is better ranked in the coalitional ranking than the cell to which the second agent belongs in the partition. We provide an axiomatic characterization of the core-partition social ranking and an algorithm to compute the associated social rankings.

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.

Properties of Solutions for Games on Union-Closed Systems

A situation in which a finite set of players can obtain certain payoffs by cooperation can be described by a cooperative game with transferable utility, or simply a TU-game. A solution for TU-games assigns a set of payoff distributions to every TU-game. In the literature, various models of games with restricted cooperation can be found where, instead of allowing all subsets of the player set N to form, it is assumed that the set of feasible coalitions is a subset of the power set of N. In this paper, we consider games on a union-closed system where the set of feasible coalitions is closed under the union, i.e., for any two feasible coalitions also, their union is feasible. Properties of solutions (the core, the nucleolus, and the prekernel) are discussed for games on a union-closed system.

Population-Dynamics-Assisted Coalitional Model Predictive Control for Parabolic-Trough Solar Plants

This paper proposes a coalitional model predictive control method for temperature regulation in parabolic-trough solar fields. The global optimization problem is divided into a set of local subproblems that will be solved in parallel by a set of coalitions. However, these local (smaller) problems remain coupled by a common global resource constraint. In this regard, we present a population-dynamics-assisted resource allocation approach to fully decouple the local optimization problems. By doing this, each coalition can address its corresponding optimization problem without relying on the solutions of the other coalitions. To illustrate the proposed methodology, we provide simulation results for a 100-loop parabolic-trough solar collector field.

Development of multi-agent information security management system

The issue of creating an information security system is very relevant in the world today. One of the urgent tasks is to solve the issues of effective protection of information from both external and internal threats through the creation and implementation of information security management systems in automated systems of enterprises, which, among other things, requires the formalization of the task of protecting information for its subsequent implementation by software and other means. Now there are security analysis systems, for example, that examine the security elements settings of workstations and servers operating systems, analyze the network topology, look for unprotected network connections, examine the settings of firewalls. The disadvantage of these systems is that they are not suitable for monitoring large volumes of network traffic. The solution to this problem is the use of monitoring tools capable of analyzing large amounts of data in real time. Therefore, a significant place in the article is given to the review of developments based on artificial intelligence technologies, namely multi-agent systems, review of information security models, threat risk assessment in automated systems.
 The functional architecture of the information security management system based on a multi-agent system has been proposed to search in real time for information security optimal solutions through the selection of such coalitions of protection mechanisms agents that will allow to build the optimal protection of the automated system according to the selected criteria. The model with complete overlapping of threats has been substantiated and adopted as a basis, which allows to analyze the overall situation and choose strategically important decisions directly during the organization of information security. The essence of of multi-agent systems functioning that implement a decentralized control system based on the work of autonomous agents that can be implemented programmatically has been revealed. The role of threat agents, resource agents, agents of protection mechanisms and their functional purpose have been defined. The problem of searching a set of protection mechanisms agents coalition for the current state of the automated system as a problem of optimal search by the criterion of protection cost, taking into account the value of information, has been generalized. Due to the modularity of the multi-agent system, the further work will be aimed at detailing its components and perfection.

Conditional satisfaction: political support, congruence, and cabinet composition

ABSTRACT This paper examines the relationship between citizen satisfaction with the functioning of democracy and ideological congruence. We focus on how this relationship may vary by government type, paying attention to the conditioning effects of coalition governments’ ideological make-up and individual-level education. Our analyses rely on harmonized survey data covering one million respondents in 28 countries over a 40-year period. We find limited evidence that the relationship between citizen satisfaction and ideological congruence is conditional on national government type. All coalitions are not, however, created equal. Comparing single-party governments to multi-party governments with different ideological compositions, we find striking differences, but only for the higher educated. While the negative relationship between citizen satisfaction and ideological incongruence is similar for lower-educated citizens in single-party and multi-party coalition settings (irrespective of cabinet composition), for the higher educated, the relationship weakens as a function of the ideological diversity of the coalition cabinet.

Coalition Formation in Games with Externalities

This paper studies an extensive form game of coalition formation with random proposers in games with externalities. It is shown that an agreement will be reached without delay if any set of coalitions profits from merging. Even under this strong condition, the equilibrium coalition structure is not necessarily efficient. There may be multiple equilibria even in the absence of externalities, and symmetric players are not necessarily treated symmetrically in equilibrium. If the grand coalition forms without delay in equilibrium, expected payoffs must be in the core of the characteristic function game that assigns to each coalition its equilibrium payoff. Compared with the rule of order process of Ray and Vohra (Games Econ Behav 26:286–336, 1999), the bargaining procedure with random proposers tends to give a large advantage to the proposer, whereas the bargaining procedure with a rule of order tends to favor the responders. The equilibria of the two procedures cannot be ranked in general in terms of efficiency.

Forming Coalitions in Normal-Form Games

For a given n-person normal-form game G, we consider all possible sets of mutually exclusive and collective exhaustive coalitions of the n players. For each such set of coalitions, we define a coalitional semi-cooperative game Γ of G as one in which 1) the coalitions are taken as the players of this new game, 2) each coalition tries to maximize the sum of its individual players’ payoffs, and 3) the players within a coalition cooperate to do so. The purpose of this paper is to determine an optimal set of coalitions for G for some relevant notion of optimality. To do so, for the payoff matrix of each possible Γ of G, we determine all Greedy Scalar Equilibria (GSEs), where a GSE is an analog of the Nash equilibrium but always exists in pure strategies. For each of these GSEs, we divide the total payoff for each coalition among its members in the same proportions as its members average over the entire payoff matrix of G. Doing so gives n modified individual player payoffs associated with each GSE of all the Γs. For each of these GSEs, we then compute the geometric mean of its n modified payoffs. A set of coalitions associated with a GSE is deemed optimal for G if the corresponding geometric mean is a maximum among all the GSEs for all the Γs. An optimal set of coalitions thus incorporates the selfishness of the coalitions via the GSE, while the geometric mean of the redistribution of the players’ payoffs models the cooperation of and the fairness for the individual players.

Tensor approximation of cooperative games and their semivalues

We propose an algorithm to approximate the semivalues of general transferable-utility cooperative games that involve a large set of players 1,…,|N| and possibly depend on uncertain parameters. We first encode the game's utility function using a low-rank tensor decomposition, namely the tensor train (TT) model, which requires a limited number of function evaluations. The TT format casts the utility as a compressed tensor of shape 2|N| and makes it possible to efficiently work with the exponentially-sized set of all possible coalitions of players. Given a game compressed in this manner, the proposed algorithm obtains arbitrary semivalues without incurring additional error, in particular the Shapley values and Banzhaf-Coleman indices, which are two of the most important allocation rules in cooperative game theory. Our algorithm takes O(|N|R2) operations per semivalue, where R is the game's TT rank. We show experimentally that many classical games can be compressed at low error with a moderate TT rank, making our algorithm more sample-efficient than Monte Carlo-based estimation. We also give a theoretical bound for the error of the semivalues obtained through our algorithm. Last, when the game depends on randomly distributed parameters, we are able to compute the expected semivalues efficiently.

Learning non-compensatory sorting models using efficient SAT/MaxSAT formulations

The Non-Compensatory Sorting model aims at assigning alternatives evaluated on multiple criteria to one of the predefined ordered categories. Computing parameters of the Non-Compensatory Sorting model compatible to a set of reference assignments is computationally demanding. To overcome this problem, two formulations based on Boolean satisfiability have recently been proposed to learn the parameters of the Non-Compensatory Sorting model from perfect preference information, i.e. when the set of reference assignments can be completely represented in the model. In this paper, two popular variants of the Non-Compensatory Sorting model are considered, the Non-Compensatory Sorting model with a unique profile and the Non-Compensatory Sorting model with a unique set of sufficient coalitions. For each variant, we start by extending the formulation based on a separation principle to the multiple category case. Moreover, we extend the two formulations to handle inconsistency in the preference information using the Maximum satisfiability problem language. A computational study is proposed to compare the efficiency of both formulations to learn the two Non-Compensatory Sorting models (with a unique profile and with a unique set of sufficient coalitions) from noiseless and noisy preference information.

Use of Fuzzy Coalition Games in Socially Oriented Decision Making During Hospitalization in Pandemic

The problems of organizing medical care in the context of the COVID-19 pandemic, associated with the uncertainty and limitedness of various resources, led to the need to improve decision-making systems for hospitalization of patients. Situational management can improve the decision-making process to fit the current situation better. At the same time, it becomes important to take into account the influence of psychological factors on decisions made during hospitalization. The paper proposes the use of coalition games for situational management during hospitalization of patients. The players and members of the coalition are hospitals, ambulance teams, patients and computed tomography centers. The goal of the game is to form a coalition of participants that provides the maximum benefit in terms of time and cost of hospitalization at the time of decision making. The general scheme of hospitalization, the main sources of information about the situation, the formulation and formalization of the problem are considered. An experiment was carried out in which the formation of a coalition during hospitalization was tested based on data obtained from analyzing the dynamics of the COVID-19 pandemic. Due to the small amount of data and the lack of approved models of the situation development, when carrying out the calculation, some of the parameters were estimated using heuristic models of the development of the situation, based on the analysis of information from open sources of information. The experiment result contains a set of coalitions that provide the maximum benefit under the specified constraints. At the same time, the calculation time of the coalition game allows using the proposed model of decision-making support during hospitalization in the dispatch service of ambulance stations.

Fairness and fuzzy coalitions

In this paper, we study the problem of a fair redistribution of resources among agents in an exchange economy á la Shitovitz (Econometrica 41:467–501, 1973), with agents’ measure space having both atoms and an atomless sector. We proceed by following the idea of Aubin (Mathematical methods of game economic theory. North-Holland, Amsterdam, New York, Oxford, 1979) to allow for partial participation of individuals in coalitions, that induces an enlargement of the set of ordinary coalitions to the so-called fuzzy or generalized coalitions. We propose a notion of fairness which, besides efficiency, imposes absence of envy towards fuzzy coalitions, and which fully characterizes competitive equilibria and Aubin-core allocations.

FACS: Fast Code-based Algorithm for Coalition Structure Generation (Student Abstract)

In this paper, we propose a new algorithm for the Coalition Structure Generation (CSG) problem that can be run with more than 28 agents while using a complete set of coalitions as input. The current state-of-the-art limit for exact algorithms to solve the CSG problem within a reasonable time is 27 agents. Our algorithm uses a novel representation of the search space and a new code-based search technique. We propose an effective heuristic search method to efficiently explore the space of coalition structures using our code based technique and show that our method outperforms existing state-of-the-art algorithms by multiple orders of magnitude.

Unfair Acts and Practices: A Revisionist History

The Federal Trade Commission Act’s ban on “unfair . . . acts and practices” would, on its face, seem to give the FTC an awesome power to define proper treatment of consumers in changing conditions. But even in a world of widespread corporate surveillance, ongoing racial discrimination, impenetrably complex financial products, pyramid schemes, and more, the unfairness authority is used rarely, mostly in egregious cases of wrongdoing. Why? The standard explanation is that the more expansive notion of unfairness was tried in the 1970s, and it failed spectacularly. The FTC of this era was staffed by bureaucrats convinced of their own moral superiority and blind to the self-correcting dynamics of the market. When the FTC finally reached too far and tried to ban television advertising of sugary cereals to children, it undermined its own legitimacy, causing Congress to put pressure on the agency to narrow its definition of unfairness. This Article argues that this standard explanation gets the law and the history wrong, and, thus, that the FTC’s unfairness authority is more potent than commonly assumed. The regulatory initiatives of the 1970s were actually quite popular. The backlash against them was led by the businesses whose profit margins they threatened. Leaders of these businesses had become increasingly radicalized and well-organized and brought their new political clout to bear on an unsuspecting FTC. It was not the re-articulation of the unfairness standard in 1980 that narrowed unfairness to its current form, but rather the subsequent takeover of the FTC by neoliberal economists and lawyers who had been supported by these radicalized business leaders. The main limitation on the use of the unfairness authority since then has been the ideology of regulators charged with its enforcement. In fact, the conventional morality tale about the FTC’s efforts in the 1970s are part of what keeps this ideology dominant. A reconsideration of the meaning of unfairness requires situating the drama of the 1970s and 80s in a longer struggle over governance of consumer markets. Since the creation of the FTC, and even before, an evolving set of coalitions have battled over what makes markets fair. These coalitions can be divided roughly into those who favor norm setting by government agencies informed by experts held accountable to democratic publics and those who favor norm setting by business leaders made accountable via the profit motive. The meaning of “unfair . . . acts and practices” has been defined and redefined through these struggles, and it can and should be redefined again to reconstruct the state capacity to define standards of fair dealing.