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  1.  58
    Ontology Merging as Social Choice.Daniele Porello & Ulle Endriss - 2014 - Journal of Logic and Computation 24 (6):1229--1249.
    The problem of merging several ontologies has important applications in the Semantic Web, medical ontology engineering and other domains where information from several distinct sources needs to be integrated in a coherent manner.We propose to view ontology merging as a problem of social choice, i.e. as a problem of aggregating the input of a set of individuals into an adequate collective decision. That is, we propose to view ontology merging as ontology aggregation. As a first step in this direction, we (...)
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  2.  94
    Complexity of Judgment Aggregation.Ulle Endriss, Umberto Grandi & Daniele Porello - 2012 - Journal of Artificial Intelligence Research 45:481--514.
    We analyse the computational complexity of three problems in judgment aggregation: (1) computing a collective judgment from a profile of individual judgments (the winner determination problem); (2) deciding whether a given agent can influence the outcome of a judgment aggregation procedure in her favour by reporting insincere judgments (the strategic manipulation problem); and (3) deciding whether a given judgment aggregation scenario is guaranteed to result in a logically consistent outcome, independently from what the judgments supplied by the individuals are (the (...)
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  3.  24
    Modelling Multilateral Negotiation in Linear Logic.Daniele Porello & Ulle Endriss - 2010 - In {ECAI} 2010 - 19th European Conference on Artificial Intelligence, Lisbon, Portugal, August 16-20, 2010, Proceedings. pp. 381--386.
    We show how to embed a framework for multilateral negotiation, in which a group of agents implement a sequence of deals concerning the exchange of a number of resources, into linear logic. In this model, multisets of goods, allocations of resources, preferences of agents, and deals are all modelled as formulas of linear logic. Whether or not a proposed deal is rational, given the preferences of the agents concerned, reduces to a question of provability, as does the question of whether (...)
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  4.  18
    Modelling Combinatorial Auctions in Linear Logic.Daniele Porello & Ulle Endriss - 2010 - In Principles of Knowledge Representation and Reasoning: Proceedings of the Twelfth International Conference, {KR} 2010, Toronto, Ontario, Canada, May 9-13, 2010.
    We show that linear logic can serve as an expressive framework in which to model a rich variety of combinatorial auction mechanisms. Due to its resource-sensitive nature, linear logic can easily represent bids in combinatorial auctions in which goods may be sold in multiple units, and we show how it naturally generalises several bidding languages familiar from the literature. Moreover, the winner determination problem, i.e., the problem of computing an allocation of goods to bidders producing a certain amount of revenue (...)
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  5.  19
    Aggregating Dependency Graphs Into Voting Agendas in Multi-Issue Elections.Stephane Airiau, Ulle Endriss, Umberto Grandi, Daniele Porello & Joel Uckelman - 2011 - In {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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