Deriving consensus in multiagent systems

Ephrati, Eithan; Rosenschein, Jeffrey S.

doi:10.1016/0004-3702(95)00105-0

Cited by 67 publications

(19 citation statements)

References 30 publications

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“…The issues of richness and exploitation we have identified in this paper apply to this mechanisms as well. Therefore, our work adds to the already many insights into the workings and application of the CTm [14].…”

Section: Related Workmentioning

confidence: 87%

Towards a Market Mechanism for Airport Traffic Control

Jonker

Meyer

Dignum

2005

Progress in Artificial Intelligence

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Abstract. We present a multiagent decision mechanism for the airport traffic control domain. It enables airlines to jointly decide on proposals for plan conflict solutions. The mechanism uses weighted voting for maximizing global utility and Clarke Tax to discourage manipulation. We introduce accounts to ensure that all agents are treated fairly, to some extent. The mechanism allows an airport to determine the pay-off between optimality and fairness of schedules. Also, it compensates for agents that happen to be in practically unfavourable positions.

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Section: Related Workmentioning

confidence: 87%

Towards a Market Mechanism for Airport Traffic Control

Jonker

Meyer

Dignum

2005

Progress in Artificial Intelligence

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“…Instead, DMs may express their preferences by imprecise formats, such as value ranges, linguistic variables and fuzzy numbers 9 . Considerable efforts have been attached to the MAGDM with inaccurate or incomplete information and many approaches to solve this problem have been reported in the existing literature 11,10,5,12,13,14,15,16,17,18,19 .…”

Section: Introductionmentioning

confidence: 99%

A decision support model for multi-attribute group decision making using a multi-objective optimization approach

Xiong¹,

Chen²,

Yang³

et al. 2013

IJCIS

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The multi-attribute group decision making (MAGDM) problem has received considerable attention in the decision analysis field and fruitful achievements have been reported in the literature. This paper focuses on the MAGDM in which the subjective absolute judgement on alternatives with respect to evaluating attributes are represented by fuzzy numbers. This paper employs the consensus degree to measure the agreement level of a MAGDM solution and develops a new measure degree-departure degree to evaluate how far the decision makers from their initial decision preferences. Based on these two conflicting measure degrees, the decision process of MAGDM is modelled as a multi-objective optimization problem. A decision support model (DSM) for MAGDM is proposed. The proposed DSM, incorporating five implementing phases, aims at obtaining acceptable decision solution(s) by solving the multi-objective optimization problem and conducting an interactive procedure with decision makers. In case study, this paper takes the alternative selection problem about hydroelectric project to illustrate the phases and procedure of the proposed DSM.

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“…On the one hand, results from voting theory have been used in AI, for example in multiagent planning (e.g., [15]) and collaborative filtering (e.g., [25]). On the other hand, AI research has made contributions to voting theory (e.g., [11,10]).…”

Section: Introductionmentioning

confidence: 99%

Decentralized voting with unconditional privacy

Brandt

Sandholm

2005

Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems

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The aggregation of conflicting preferences is a key issue in multiagent systems. Due to its universality, voting has a central role among preference aggregation mechanisms. Voting among a set of alternatives can be used for such diverse tasks as choosing a joint plan in a multiagent system, determining a leader in a group of humans or agents, or voting among different resource or task allocations. Maintaining privacy of individuals' votes is crucial in order to guarantee freedom of choice (e.g., lack of vote coercing and reputation effects), and not facilitate strategic voting. We investigate whether unconditional full privacy can be achieved in voting, that is, privacy that relies neither on trusted third parties (or on a certain fraction of the voters being trusted), nor on computational intractability assumptions (such as the hardness of factoring). In particular, we study the existence of distributed protocols that allow voters to jointly determine the outcome of an election without revealing any information but the election outcome. We show the impossibility of reaching unconditional full privacy for a variety of the most common voting schemes ranging from simple veto voting to the single transferable vote scheme. On the positive side, we propose several distributed protocols that privately compute the outcome of common voting schemes while only revealing a limited amount of information.

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Deriving consensus in multiagent systems

Cited by 67 publications

References 30 publications

Towards a Market Mechanism for Airport Traffic Control

Towards a Market Mechanism for Airport Traffic Control

A decision support model for multi-attribute group decision making using a multi-objective optimization approach

Decentralized voting with unconditional privacy

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