Results 1  10
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50
A short introduction to computational social choice
 Proc. 33rd Conference on Current Trends in Theory and Practice of Computer Science
, 2007
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Complexity of Constructing Solutions in the Core Based on Synergies among Coalitions
 ARTIFICIAL INTELLIGENCE
, 2006
"... Coalition formation is a key problem in automated negotiation among selfinterested agents, and other multiagent applications. A coalition of agents can sometimes accomplish things that the individual agents cannot, or can accomplish them more efficiently. Motivating the agents to abide by a solut ..."
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Cited by 34 (1 self)
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Coalition formation is a key problem in automated negotiation among selfinterested agents, and other multiagent applications. A coalition of agents can sometimes accomplish things that the individual agents cannot, or can accomplish them more efficiently. Motivating the agents to abide by a solution requires careful analysis: only some of the solutions are stable in the sense that no group of agents is motivated to break off and form a new coalition. This constraint has been studied extensively in cooperative game theory: the set of solutions that satisfy it is known as the core. The computational questions around the core have received less attention. When it comes to coalition formation among software agents (that represent realworld parties), these questions become increasingly explicit. In this
Modelbased overlapping clustering
 In KDD
, 2005
"... While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters have come from work on analysis of biological datasets. In this paper, we interpret an overlapping clustering model prop ..."
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Cited by 29 (6 self)
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While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters have come from work on analysis of biological datasets. In this paper, we interpret an overlapping clustering model proposed by Segal et al. [23] as a generalization of Gaussian mixture models, and we extend it to an overlapping clustering model based on mixtures of any regular exponential family distribution and the corresponding Bregman divergence. We provide the necessary algorithm modifications for this extension, and present results on synthetic data as well as subsets of 20Newsgroups and EachMovie datasets.
Coalitional games in open anonymous environments
 In AAAI
, 2005
"... Coalition formation is a key aspect of automated negotiation among selfinterested agents. In order for coalitions to be stable, a key question that must be answered is how the gains from cooperation are to be distributed. Various solution concepts (such as the Shapley value, core, least core, and n ..."
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Cited by 27 (7 self)
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Coalition formation is a key aspect of automated negotiation among selfinterested agents. In order for coalitions to be stable, a key question that must be answered is how the gains from cooperation are to be distributed. Various solution concepts (such as the Shapley value, core, least core, and nucleolus) have been proposed. In this paper, we demonstrate how these concepts are vulnerable to various kinds of manipulations in open anonymous environments such as the Internet. These manipulations include submitting false names (one acting as many), collusion (many acting as one), and the hiding of skills. To address these threats, we introduce a new solution concept called the anonymityproof core, which is robust to these manipulations. We show that the anonymityproof core is characterized by certain simple axiomatic conditions. Furthermore, we show that by relaxing these conditions, we obtain a concept called the least anonymityproof core, which is guaranteed to be nonempty. We also show that computational hardness of manipulation may provide an alternative barrier to manipulation.
On the computational complexity of coalitional resource games
 Artificial Intelligence
"... www.elsevier.com/locate/artint We study Coalitional Resource Games (CRGs), a variation of Qualitative Coalitional Games (QCGs) in which each agent is endowed with a set of resources, and the ability of a coalition to bring about a set of goals depends on whether they are collectively endowed with th ..."
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Cited by 26 (6 self)
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www.elsevier.com/locate/artint We study Coalitional Resource Games (CRGs), a variation of Qualitative Coalitional Games (QCGs) in which each agent is endowed with a set of resources, and the ability of a coalition to bring about a set of goals depends on whether they are collectively endowed with the necessary resources. We investigate and classify the computational complexity of a number of natural decision problems for CRGs, over and above those previously investigated for QCGs in general. For example, we show that the complexity of determining whether conflict is inevitable between two coalitions with respect to some stated resource bound (i.e., a limit value for every resource) is coNPcomplete. We then investigate the relationship between CRGs and QCGs, and in particular the extent to which it is possible to translate between the two models. We first characterise the complexity of determining equivalence between CRGs and QCGs. We then show that it is always possible to translate any given CRG into a succinct equivalent QCG, and that it is not always possible to translate a QCG into an equivalent CRG; we establish some necessary and some sufficient conditions for a translation from QCGs to CRGs to be possible, and show that even where an equivalent CRG exists, it may have size exponential in the number of goals and agents of its source QCG.
Coalitional Skill Games
"... We consider Coalitional Skill Games (CSGs), a simple model of cooperation among agents. This is a restricted form of coalitional games, where each agent has a set of skills that are required to complete various tasks. Each task requires a set of skills in order to be completed, and a coalition can a ..."
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Cited by 19 (8 self)
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We consider Coalitional Skill Games (CSGs), a simple model of cooperation among agents. This is a restricted form of coalitional games, where each agent has a set of skills that are required to complete various tasks. Each task requires a set of skills in order to be completed, and a coalition can accomplish the task only if the coalition’s agents cover the set of required skills for the task. The gain for a coalition depends only on the subset of tasks it can complete. We consider the computational complexity of several problems in CSGs, for example, testing if an agent is a dummy or veto agent, computing the core of the game or testing whether the core is empty, and finding the Shapley value or Banzhaf power index of agents.
Coalition Structure Generation Utilizing Compact Characteristic Function Representations (Extended Abstract)
"... Forming e ective coalitions is a major research challenge in AI and multiagent systems. Coalition structure generation (CSG), which involves partitioning a set of agents into coalitions so that social surplus is maximized, is a central research topic due to its computational complexity. In this pap ..."
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Cited by 17 (3 self)
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Forming e ective coalitions is a major research challenge in AI and multiagent systems. Coalition structure generation (CSG), which involves partitioning a set of agents into coalitions so that social surplus is maximized, is a central research topic due to its computational complexity. In this paper, we present new methods for CSG utilizing recently developed compact representation schemes for characteristic functions. We characterize the complexity of CSG under these representation schemes. In this context, the complexity is driven more by the number of synergy coalition groups than by the number of agents. Furthermore, we develop mixed integer programming formulations and show that an otheshelf optimization package can solve these problems quite e ciently.
A compact representation scheme for coalitional games in open anonymous environments
 In AAAI
, 2006
"... Coalition formation is an important capability of automated negotiation among selfinterested agents. In order for coalitions to be stable, a key question that must be answered is how the gains from cooperation are to be distributed. Recent research has revealed that traditional solution concepts, s ..."
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Cited by 16 (4 self)
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Coalition formation is an important capability of automated negotiation among selfinterested agents. In order for coalitions to be stable, a key question that must be answered is how the gains from cooperation are to be distributed. Recent research has revealed that traditional solution concepts, such as the Shapley value, core, least core, and nucleolus, are vulnerable to various manipulations in open anonymous environments such as the Internet. These manipulations include submitting false names, collusion, and hiding some skills. To address this, a solution concept called the anonymityproof core, which is robust against such manipulations, was developed. However, the representation size of the outcome function in the anonymityproof core (and similar concepts) requires space exponential in the number of agents/skills. This paper proposes a compact representation of the outcome function, given that the characteristic function is represented using a recently introduced compact language that explicitly specifies only coalitions that introduce synergy. This compact representation scheme can successfully express the outcome function in the anonymityproof core. Furthermore, this paper develops a new solution concept, the anonymityproof nucleolus, that is also expressible in this compact representation. We show that the anonymityproof nucleolus always exists, is unique, and is in the anonymityproof core (if the latter is nonempty), and assigns the same value to symmetric skills.
Divide and Conquer: FalseName Manipulations in Weighted Voting Games
, 2008
"... In this paper, we study falsename manipulations in weighted voting games. Weighted voting is a wellknown model of cooperation among agents in decisionmaking domains. In such games, each of the players has a weight, and a coalition of players wins the game if its total weight exceeds a certain quo ..."
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Cited by 16 (7 self)
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In this paper, we study falsename manipulations in weighted voting games. Weighted voting is a wellknown model of cooperation among agents in decisionmaking domains. In such games, each of the players has a weight, and a coalition of players wins the game if its total weight exceeds a certain quota. While a player’s ability to influence the outcome of the game is related to its weight, it is not always directly proportional to it. This observation has led to the concept of a power index, which is a measure of an agent’s “real power ” in this domain. One prominent power index is the Shapley–Shubik index, which has been widely used to analyze political power. This index is equal to the Shapley value of the player in the game. If an agent can alter the game so that his Shapley–Shubik index increases, this will mean that he has gained power in the game. Moreover,
A Tractable and Expressive Class of Marginal Contribution Nets and Its Applications
, 2008
"... Coalitional games raise a number of important questions from the point of view of computer science, key among them being how to represent such games compactly, and how to efficiently compute solution concepts assuming such representations. Marginal contribution nets (MCnets), introduced by Ieong an ..."
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Cited by 14 (1 self)
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Coalitional games raise a number of important questions from the point of view of computer science, key among them being how to represent such games compactly, and how to efficiently compute solution concepts assuming such representations. Marginal contribution nets (MCnets), introduced by Ieong and Shoham, are one of the simplest and most influential representation schemes for coalitional games. MCnets are a rulebased formalism, in which rules take the form pattern − → value, where “pattern ” is a Boolean condition over agents, and “value ” is a numeric value. Ieong and Shoham showed that, for a class of what we will call “basic” MCnets, where patterns are constrained to be a conjunction of literals, marginal contribution nets permit the easy computation of solution concepts such as the Shapley value. However, there are very natural classes of coalitional game that