The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Tonghui Wang - One of the best experts on this subject based on the ideXlab platform.
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Computational Aspects of the coarsening at random model and the Shapley value
Information Sciences, 2007Co-Authors: Tonghui WangAbstract:This paper is concerned with Computational Aspects of coarse data in information technology. A method for calculating the CAR (coarsening at random) model of a finite random set is obtained, and a formula for computing the Shapley value using the distribution of the random set is given. The relationship between the CAR model solution and the Shapley value is also discussed. Several examples are given to illustrate our results.
Toby Walsh - One of the best experts on this subject based on the ideXlab platform.
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Computational Aspects of multi winner approval voting
Adaptive Agents and Multi-Agents Systems, 2015Co-Authors: Haris Aziz, Serge Gaspers, Joachim Gudmundsson, Simon Mackenzie, Nicholas Mattei, Toby WalshAbstract:We study Computational Aspects of three prominent voting rules that use approval ballots to select multiple winners. These rules are proportional approval voting, reweighted approval voting, and satisfaction approval voting. Each rule is designed with the intention to compute a representative winning set. We show that computing the winner for proportional approval voting is NP-hard, closing an open problem (Kilgour, 2010). As none of the rules we examine are strategy-proof, we study various strategic Aspects of the rules. In particular, we examine the Computational complexity of computing a best response for both a single agent and a group of agents. In many settings, we show that it is NP-hard for an agent or agents to compute how best to vote given a fixed set of approval ballots of the other agents.
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Computational Aspects of Multi-Winner Approval Voting
arXiv: Computer Science and Game Theory, 2014Co-Authors: Haris Aziz, Serge Gaspers, Joachim Gudmundsson, Simon Mackenzie, Nicholas Mattei, Toby WalshAbstract:We study Computational Aspects of three prominent voting rules that use approval ballots to elect multiple winners. These rules are satisfaction approval voting, proportional approval voting, and reweighted approval voting. We first show that computing the winner for proportional approval voting is NP-hard, closing a long standing open problem. As none of the rules are strategyproof, even for dichotomous preferences, we study various strategic Aspects of the rules. In particular, we examine the Computational complexity of computing a best response for both a single agent and a group of agents. In many settings, we show that it is NP-hard for an agent or agents to compute how best to vote given a fixed set of approval ballots from the other agents.
Michael Havbro Faber - One of the best experts on this subject based on the ideXlab platform.
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Computational Aspects of risk-based inspection planning
Computer-Aided Civil and Infrastructure Engineering, 2006Co-Authors: Daniel Straub, Michael Havbro FaberAbstract:The significant Computational efforts required to compute risk-based inspection plans founded on the Bayesian decision theory has hindered their application in the past. In this article, a Computationally efficient method for the calculation of risk-based inspection (RBI) plans is presented, which overcomes the problem through the use of a generic approach. After an introduction in RBI planning, focus is set on the Computational Aspects of the methodology. The derivation of inspection plans through interpolation in databases with predefined generic inspection plans is demonstrated and the accuracy of the methodology is investigated. Finally, an overview is given on some recent applications of the generic approach in practice, including the implementation in efficient software tools.
Haris Aziz - One of the best experts on this subject based on the ideXlab platform.
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Computational Aspects of multi winner approval voting
Adaptive Agents and Multi-Agents Systems, 2015Co-Authors: Haris Aziz, Serge Gaspers, Joachim Gudmundsson, Simon Mackenzie, Nicholas Mattei, Toby WalshAbstract:We study Computational Aspects of three prominent voting rules that use approval ballots to select multiple winners. These rules are proportional approval voting, reweighted approval voting, and satisfaction approval voting. Each rule is designed with the intention to compute a representative winning set. We show that computing the winner for proportional approval voting is NP-hard, closing an open problem (Kilgour, 2010). As none of the rules we examine are strategy-proof, we study various strategic Aspects of the rules. In particular, we examine the Computational complexity of computing a best response for both a single agent and a group of agents. In many settings, we show that it is NP-hard for an agent or agents to compute how best to vote given a fixed set of approval ballots of the other agents.
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Computational Aspects of Multi-Winner Approval Voting
arXiv: Computer Science and Game Theory, 2014Co-Authors: Haris Aziz, Serge Gaspers, Joachim Gudmundsson, Simon Mackenzie, Nicholas Mattei, Toby WalshAbstract:We study Computational Aspects of three prominent voting rules that use approval ballots to elect multiple winners. These rules are satisfaction approval voting, proportional approval voting, and reweighted approval voting. We first show that computing the winner for proportional approval voting is NP-hard, closing a long standing open problem. As none of the rules are strategyproof, even for dichotomous preferences, we study various strategic Aspects of the rules. In particular, we examine the Computational complexity of computing a best response for both a single agent and a group of agents. In many settings, we show that it is NP-hard for an agent or agents to compute how best to vote given a fixed set of approval ballots from the other agents.
Annette Meidell - One of the best experts on this subject based on the ideXlab platform.
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Some Computational Aspects of iterated structures
Composites Part B: Engineering, 2001Co-Authors: Johan Byström, Johan Helsing, Annette MeidellAbstract:We consider some Computational Aspects of effective properties for some multi-scale structures. In particular, we discuss iterated square honeycombs and another type of square honeycombs containing up to 4000 small discs randomly distributed inside each square. We present some numerical methods for estimating the effective conductivity with good control of the accuracy.
