Titlebook: Algorithmic Decision Theory; Third International Patrice Perny,Marc Pirlot,Alexis Tsoukiàs Conference proceedings 2013 Springer-Verlag Ber

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penance

Burak Emir,Sebastian Maneth,Martin Oderskyms can be characterised, designed, chosen or justified. The framework shows that 5 features are necessary and sufficient in order to completely describe the whole set of existing methods. It also explains why optimisation remains the general approach under which decision problems are algorithmically considered.

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Didier Buchs,Luis Pedro,Levi Lúciortain about the current state of the world and thus about the effect that the chosen action would have. Each voter has preferences about what state they would like to see reached once the action has been executed. That is, we need to integrate two kinds of aggregation: beliefs regarding the current state and preferences regarding the next state.

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Qingguo Xu,Robert de Simone,Julien DeAntonicepted or rejected. Each voter supports a certain subset of the proposals–the . of this voter–and opposes the remaining ones. He accepts a ballot if he supports more than half of the proposals in this ballot. The task is to decide whether there exists a ballot approving a set of selected proposals (

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Xuandong Li,Zhiming Liu,Wang Yi problem in the lexicographic ordering approach (LO). Like all multicriteria optimization methods, the LO method has the criteria order parameter that should be fixed carefully. Indeed, the criteria usually conflict with each other, and thus, finding an appropriate order between the criteria is chal

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Ben Moszkowski,Dimitar P. Gueleve say about the possible (co-)winners? The outcome depends on the number of candidates each voter will approve. Whereas it is easy to know who can be a unique winner, we show that deciding whether a set of at least two candidates can be the set of co-winners is computationally hard. If, in addition,

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https://doi.org/10.1007/978-3-319-25942-0manipulation, we in particular consider incomplete judgment sets and the notions of top-respecting and closeness-respecting preferences introduced by Dietrich and List [13]. This complements previous work on the complexity of manipulation in judgment aggregation that focused on Hamming-distance-indu