1,148 research outputs found

    Experimental Analysis of the Effects of Manipulations in Weighted Voting Games

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    Weighted voting games are classic cooperative games which provide compact representation for coalition formation models in human societies and multiagent systems. As useful as weighted voting games are in modeling cooperation among players, they are, however, not immune from the vulnerability of manipulations (i.e., dishonest behaviors) by strategic players that may be present in the games. With the possibility of manipulations, it becomes difficult to establish or maintain trust, and, more importantly, it becomes difficult to assure fairness in such games. For these reasons, we conduct careful experimental investigations and analyses of the effects of manipulations in weighted voting games, including those of manipulation by splitting, merging, and annexation . These manipulations involve an agent or some agents misrepresenting their identities in anticipation of gaining more power or obtaining a higher portion of a coalition\u27s profits at the expense of other agents in a game. We consider investigation of some criteria for the evaluation of game\u27s robustness to manipulation. These criteria have been defined on the basis of theoretical and experimental analysis. For manipulation by splitting, we provide empirical evidence to show that the three prominent indices for measuring agents\u27 power, Shapley-Shubik, Banzhaf, and Deegan-Packel, are all susceptible to manipulation when an agent splits into several false identities. We extend a previous result on manipulation by splitting in exact unanimity weighted voting games to the Deegan-Packel index, and present new results for excess unanimity weighted voting games. We partially resolve an important open problem concerning the bounds on the extent of power that a manipulator may gain when it splits into several false identities in non-unanimity weighted voting games. Specifically, we provide the first three non-trivial bounds for this problem using the Shapley-Shubik and Banzhaf indices. One of the bounds is also shown to be asymptotically tight. Furthermore, experiments on non-unanimity weighted voting games show that the three indices are highly susceptible to manipulation via annexation while they are less susceptible to manipulation via merging. Given that the problems of calculating the Shapley-Shubik and Banzhaf indices for weighted voting games are NP-complete, we show that, when the manipulators\u27 coalitions sizes are restricted to a small constant, manipulators need to do only a polynomial amount of work to find a much improved power gain for both merging and annexation, and then present two enumeration-based pseudo-polynomial algorithms that manipulators can use. Finally, we argue and provide empirical evidence to show that despite finding the optimal beneficial merge is an NP-hard problem for both the Shapley-Shubik and Banzhaf indices, finding beneficial merge is relatively easy in practice. Also, while it appears that we may be powerless to stop manipulation by merging for a given game, we suggest a measure, termed quota ratio, that the game designer may be able to control. Thus, we deduce that a high quota ratio decreases the number of beneficial merges

    False-Name Manipulation in Weighted Voting Games is Hard for Probabilistic Polynomial Time

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    False-name manipulation refers to the question of whether a player in a weighted voting game can increase her power by splitting into several players and distributing her weight among these false identities. Analogously to this splitting problem, the beneficial merging problem asks whether a coalition of players can increase their power in a weighted voting game by merging their weights. Aziz et al. [ABEP11] analyze the problem of whether merging or splitting players in weighted voting games is beneficial in terms of the Shapley-Shubik and the normalized Banzhaf index, and so do Rey and Rothe [RR10] for the probabilistic Banzhaf index. All these results provide merely NP-hardness lower bounds for these problems, leaving the question about their exact complexity open. For the Shapley--Shubik and the probabilistic Banzhaf index, we raise these lower bounds to hardness for PP, "probabilistic polynomial time", and provide matching upper bounds for beneficial merging and, whenever the number of false identities is fixed, also for beneficial splitting, thus resolving previous conjectures in the affirmative. It follows from our results that beneficial merging and splitting for these two power indices cannot be solved in NP, unless the polynomial hierarchy collapses, which is considered highly unlikely

    Structural Control in Weighted Voting Games

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    Inspired by the study of control scenarios in elections and complementing manipulation and bribery settings in cooperative games with transferable utility, we introduce the notion of structural control in weighted voting games. We model two types of influence, adding players to and deleting players from a game, with goals such as increasing a given player\u27s Shapley-Shubik or probabilistic Penrose-Banzhaf index in relation to the original game. We study the computational complexity of the problems of whether such structural changes can achieve the desired effect

    Algorithmic and complexity aspects of simple coalitional games

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    Simple coalitional games are a fundamental class of cooperative games and voting games which are used to model coalition formation, resource allocation and decision making in computer science, artificial intelligence and multiagent systems. Although simple coalitional games are well studied in the domain of game theory and social choice, their algorithmic and computational complexity aspects have received less attention till recently. The computational aspects of simple coalitional games are of increased importance as these games are used by computer scientists to model distributed settings. This thesis fits in the wider setting of the interplay between economics and computer science which has led to the development of algorithmic game theory and computational social choice. A unified view of the computational aspects of simple coalitional games is presented here for the first time. Certain complexity results also apply to other coalitional games such as skill games and matching games. The following issues are given special consideration: influence of players, limit and complexity of manipulations in the coalitional games and complexity of resource allocation on networks. The complexity of comparison of influence between players in simple games is characterized. The simple games considered are represented by winning coalitions, minimal winning coalitions, weighted voting games or multiple weighted voting games. A comprehensive classification of weighted voting games which can be solved in polynomial time is presented. An efficient algorithm which uses generating functions and interpolation to compute an integer weight vector for target power indices is proposed. Voting theory, especially the Penrose Square Root Law, is used to investigate the fairness of a real life voting model. Computational complexity of manipulation in social choice protocols can determine whether manipulation is computationally feasible or not. The computational complexity and bounds of manipulation are considered from various angles including control, false-name manipulation and bribery. Moreover, the computational complexity of computing various cooperative game solutions of simple games in dierent representations is studied. Certain structural results regarding least core payos extend to the general monotone cooperative game. The thesis also studies a coalitional game called the spanning connectivity game. It is proved that whereas computing the Banzhaf values and Shapley-Shubik indices of such games is #P-complete, there is a polynomial time combinatorial algorithm to compute the nucleolus. The results have interesting significance for optimal strategies for the wiretapping game which is a noncooperative game defined on a network

    Collective decision-making with goals

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    Des agents devant prendre une décision collective sont souvent motivés par des buts individuels. Dans ces situations, deux aspects clés doivent être abordés : sélectionner une alternative gagnante à partir des voix des agents et s'assurer que les agents ne manipulent pas le résultat. Cette thèse étudie l'agrégation et la dimension stratégique des décisions collectives lorsque les agents utilisent un langage représenté de manière compacte. Nous étudions des langages de type logique : de la logique propositionnelle aux CP-nets généralisés, en passant par la logique temporelle linéaire (LTL). Notre principale contribution est l'introduction d'un cadre de vote sur les buts, dans lequel les agents soumettent des buts individuels exprimés comme des formules de la logique propositionnelle. Les fonctions d'agrégation classiques issues du vote, de l'agrégation de jugements et de la fusion de croyances sont adaptées et étudiées de manière axiomatique et computationnelle. Les propriétés axiomatiques connues dans la littérature sur la théorie du choix social sont généralisées à ce nouveau type d'entrée, ainsi que les problèmes de complexité visant à déterminer le résultat du vote. Une autre contribution importante est l'étude de l'agrégation des CP-nets généralisés, c'est-à-dire des CP-nets où la précondition de l'énoncé de préférence est une formule propositionnelle. Nous utilisons différents agrégateurs pour obtenir un classement collectif des résultats possibles. Grâce à cette thèse, deux axes de recherche sont ainsi reliés : l'agrégation des CP-nets classiques et la généralisation des CP-nets à des préconditions incomplètes. Nous contribuons également à l'étude du comportement stratégique dans des contextes de prise de décision collective et de théorie des jeux. Le cadre du vote basé sur les buts est de nouveau étudié sous l'hypothèse que les agents peuvent décider de mentir sur leur but s'ils obtiennent ainsi un meilleur résultat. L'accent est mis sur trois règles de vote majoritaires qui se révèlent manipulables. Par conséquent, nous étudions des restrictions à la fois sur le langage des buts et sur les stratégies des agents en vue d'obtenir des résultats de votes non manipulables. Nous présentons par ailleurs une extension stratégique d'un modèle récent de diffusion d'opinion sur des réseaux d'influence. Dans les jeux d'influence définis ici, les agents ont comme but des formules en LTL et ils peuvent choisir d'utiliser leur pouvoir d'influence pour s'assurer que leur but est atteint. Des solutions classiques telles que la stratégie gagnante sont étudiées pour les jeux d'influence, en relation avec la structure du réseau et les buts des agents. Enfin, nous introduisons une nouvelle classe de concurrent game structures (CGS) dans laquelle les agents peuvent avoir un contrôle partagé sur un ensemble de variables propositionnelles. De telles structures sont utilisées pour interpréter des formules de logique temporelle en temps alternés (ATL), grâce auxquelles on peut exprimer l'existence d'une stratégie gagnante pour un agent dans un jeu itéré (comme les jeux d'influence mentionnés ci-dessus). Le résultat principal montre qu'un CGS avec contrôle partagé peut être représenté comme un CGS avec contrôle exclusif. En conclusion, cette thèse contribue au domaine de la prise de décision collective en introduisant un nouveau cadre de vote basé sur des buts propositionnels. Elle présente une étude de l'agrégation des CP-nets généralisés et une extension d'un cadre de diffusion d'opinion avec des agents rationnels qui utilisent leur pouvoir d'influence. Une réduction du contrôle partagé à un contrôle exclusif dans les CGS pour l'interprétation des logiques du raisonnement stratégique est également proposée. Par le biais de langages logiques divers, les agents peuvent ainsi exprimer buts et préférences sur la décision à prendre, et les propriétés souhaitées pour le processus de décision peuvent en être garanties.Agents having to take a collective decision are often motivated by individual goals. In such scenarios, two key aspects need to be addressed. The first is defining how to select a winning alternative from the expressions of the agents. The second is making sure that agents will not manipulate the outcome. Agents should also be able to state their goals in a way that is expressive, yet not too burdensome. This dissertation studies the aggregation and the strategic component of multi-agent collective decisions where the agents use a compactly represented language. The languages we study are all related to logic: from propositional logic, to generalized CP-nets and linear temporal logic (LTL). Our main contribution is the introduction of the framework of goal-based voting, where agents submit individual goals expressed as formulas of propositional logic. Classical aggregation functions from voting, judgment aggregation, and belief merging are adapted to this setting and studied axiomatically and computationally. Desirable axiomatic properties known in the literature of social choice theory are generalized to this new type of propositional input, as well as the standard complexity problems aimed at determining the result. Another important contribution is the study of the aggregation of generalized CP-nets coming from multiple agents, i.e., CP-nets where the precondition of the preference statement is a propositional formula. We use different aggregators to obtain a collective ordering of the possible outcomes. Thanks to this thesis, two lines of research are thus bridged: the one on the aggregation of complete CP-nets, and the one on the generalization of CP-nets to incomplete preconditions. We also contribute to the study of strategic behavior in both collective decision-making and game-theoretic settings. The framework of goal-based voting is studied again under the assumption that agents can now decide to submit an untruthful goal if by doing so they can get a better outcome. The focus is on three majoritarian voting rules which are found to be manipulable. Therefore, we study restrictions on both the language of the goals and on the strategies allowed to the agents to discover islands of strategy-proofness. We also present a game-theoretic extension of a recent model of opinion diffusion over networks of influence. In the influence games defined here, agents hold goals expressed as formulas of LTL and they can choose whether to use their influence power to make sure that their goal is satisfied. Classical solution concepts such as weak dominance and winning strategy are studied for influence games, in relation to the structure of the network and the goals of the agents. Finally, we introduce a novel class of concurrent game structures (CGS) in which agents can have shared control over a set of propositional variables. Such structures are used for the interpretation of formulas of alternating-time temporal logic, thanks to which we can express the existence of a winning strategy for an agent in a repeated game (as, for instance, the influence games mentioned above). The main result shows by means of a clever construction that a CGS with shared control can be represented as a CGS with exclusive control. In conclusion, this thesis provides a valuable contribution to the field of collective decision-making by introducing a novel framework of voting based on individual propositional goals, it studies for the first time the aggregation of generalized CP-nets, it extends a framework of opinion diffusion by modelling rational agents who use their influence power as they see fit, and it provides a reduction of shared to exclusive control in CGS for the interpretation of logics of strategic reasoning. By using different logical languages, agents can thus express their goals and preferences over the decision to be taken, and desirable properties of the decision process can be ensured

    Algorithmic and complexity aspects of simple coalitional games

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    Simple coalitional games are a fundamental class of cooperative games and voting games which are used to model coalition formation, resource allocation and decision making in computer science, artificial intelligence and multiagent systems. Although simple coalitional games are well studied in the domain of game theory and social choice, their algorithmic and computational complexity aspects have received less attention till recently. The computational aspects of simple coalitional games are of increased importance as these games are used by computer scientists to model distributed settings. This thesis fits in the wider setting of the interplay between economics and computer science which has led to the development of algorithmic game theory and computational social choice. A unified view of the computational aspects of simple coalitional games is presented here for the first time. Certain complexity results also apply to other coalitional games such as skill games and matching games. The following issues are given special consideration: influence of players, limit and complexity of manipulations in the coalitional games and complexity of resource allocation on networks. The complexity of comparison of influence between players in simple games is characterized. The simple games considered are represented by winning coalitions, minimal winning coalitions, weighted voting games or multiple weighted voting games. A comprehensive classification of weighted voting games which can be solved in polynomial time is presented. An efficient algorithm which uses generating functions and interpolation to compute an integer weight vector for target power indices is proposed. Voting theory, especially the Penrose Square Root Law, is used to investigate the fairness of a real life voting model. Computational complexity of manipulation in social choice protocols can determine whether manipulation is computationally feasible or not. The computational complexity and bounds of manipulation are considered from various angles including control, false-name manipulation and bribery. Moreover, the computational complexity of computing various cooperative game solutions of simple games in dierent representations is studied. Certain structural results regarding least core payos extend to the general monotone cooperative game. The thesis also studies a coalitional game called the spanning connectivity game. It is proved that whereas computing the Banzhaf values and Shapley-Shubik indices of such games is #P-complete, there is a polynomial time combinatorial algorithm to compute the nucleolus. The results have interesting significance for optimal strategies for the wiretapping game which is a noncooperative game defined on a network.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Forms of representation for simple games: sizes, conversions and equivalences

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    Simple games are cooperative games in which the benefit that a coalition may have is always binary, i.e., a coalition may either win or loose. This paper surveys different forms of representation of simple games, and those for some of their subfamilies like regular games and weighted games. We analyze the forms of representations that have been proposed in the literature based on different data structures for sets of sets. We provide bounds on the computational resources needed to transform a game from one form of representation to another one. This includes the study of the problem of enumerating the fundamental families of coalitions of a simple game. In particular we prove that several changes of representation that require exponential time can be solved with polynomial-delay and highlight some open problems.Peer ReviewedPostprint (author’s final draft

    The shared assignment game and applications to pricing in cloud computing

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    ABSTRACT We propose an extension to the Assignment Gam

    Coalition structure generation over graphs

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    We give the analysis of the computational complexity of coalition structure generation over graphs. Given an undirected graph G = (N,E) and a valuation function v : P(N) → R over the subsets of nodes, the problem is to find a partition of N into connected subsets, that maximises the sum of the components values. This problem is generally NP-complete; in particular, it is hard for a defined class of valuation functions which are independent of disconnected members — that is, two nodes have no effect on each others marginal contribution to their vertex separator. Nonetheless, for all such functions we provide bounds on the complexity of coalition structure generation over general and minor free graphs. Our proof is constructive and yields algorithms for solving corresponding instances of the problem. Furthermore, we derive linear time bounds for graphs of bounded treewidth. However, as we show, the problem remains NP-complete for planar graphs, and hence, for any Kk minor free graphs where k ≥ 5. Moreover, a 3-SAT problem with m clauses can be represented by a coalition structure generation problem over a planar graph with O(m2) nodes. Importantly, our hardness result holds for a particular subclass of valuation functions, termed edge sum, where the value of each subset of nodes is simply determined by the sum of given weights of the edges in the induced subgraph
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