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  1.  28
    Representing Utility Functions via Weighted Goals.Joel Uckelman, Yann Chevaleyre, Ulle Endriss & Jérôme Lang - 2009 - Mathematical Logic Quarterly 55 (4):341-361.
    We analyze the expressivity, succinctness, and complexity of a family of languages based on weighted propositional formulas for the representation of utility functions. The central idea underlying this form of preference modeling is to associate numerical weights with goals specified in terms of propositional formulas, and to compute the utility value of an alternative as the sum of the weights of the goals it satisfies. We define a large number of representation languages based on this idea, each characterized by a (...)
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  2.  78
    Modal and temporal logics for abstract space–time structures.Sara L. Uckelman & Joel Uckelman - 2007 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 38 (3):673-681.
    In the 4th century BC, the Greek philosopher Diodoros Chronos gave a temporal definition of necessity. Because it connects modality and temporality, this definition is of interest to philosophers working within branching time or branching space-time models. This definition of necessity can be formalized and treated within a logical framework. We give a survey of the several known modal and temporal logics of abstract space-time structures based on the real numbers and the integers, considering three different accessibility relations between spatio-temporal (...)
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  3. Aggregating Dependency Graphs into Voting Agendas in Multi-Issue Elections.Stephane Airiau, Ulle Endriss, Umberto Grandi, Daniele Porello & Joel Uckelman - 2011 - In Stephane Airiau, Ulle Endriss, Umberto Grandi, Daniele Porello & Joel Uckelman (eds.), {IJCAI} 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, Catalonia, Spain, July 16-22, 2011. pp. 18--23.
    Many collective decision making problems have a combinatorial structure: the agents involved must decide on multiple issues and their preferences over one issue may depend on the choices adopted for some of the others. Voting is an attractive method for making collective decisions, but conducting a multi-issue election is challenging. On the one hand, requiring agents to vote by expressing their preferences over all combinations of issues is computationally infeasible; on the other, decomposing the problem into several elections on smaller (...)
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  4. {IJCAI} 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, Catalonia, Spain, July 16-22, 2011.Stephane Airiau, Ulle Endriss, Umberto Grandi, Daniele Porello & Joel Uckelman (eds.) - 2011
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  5.  13
    Compactly representing utility functions using weighted goals and the max aggregator.Joel Uckelman & Ulle Endriss - 2010 - Artificial Intelligence 174 (15):1222-1246.
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