Binary Aggregation with Integrity Constraints

Grandi, Umberto; Endriss, Ulrich

doi:10.5591/978-1-57735-516-8/IJCAI11-045

Binary Aggregation with Integrity Constraints

Umberto Grandi, Ulrich Endriss

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 204-208.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-045

Abstract

Binary aggregation studies problems in which individuals express yes/no choices over a number of possibly correlated issues, and these individual choices need to be aggregated into a collective choice. We show how several classical frameworks of Social Choice Theory, particularly preference and judgment aggregation, can be viewed as binary aggregation problems by designing an appropriate set of integrity constraints for each specific setting. We explore the generality of this framework, showing that it makes available useful techniques both to prove theoretical results, such as a new impossibility theorem in preference aggregation, and to analyse practical problems, such as the characterisation of safe agendas in judgment aggregation in a syntactic way. The framework also allows us to formulate a general definition of paradox that is independent of the domain under consideration, which gives rise to the study of the class of aggregation procedures of generalised dictatorships.

Umberto Grandi, and Ulrich Endriss. 2011. Binary Aggregation with Integrity Constraints. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 204–208. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-045

@inproceedings{ijcai2011p45,
  title     = {Binary Aggregation with Integrity Constraints},
  author    = {Grandi, Umberto and Endriss, Ulrich},
  booktitle = {Proceedings of the Twenty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-11}},
  publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
  editor    = {Toby Walsh},
  pages     = {204--208},
  year      = {2011},
  month     = {7},
  doi       = {10.5591/978-1-57735-516-8/IJCAI11-045},
  url       = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-045},
}

TY  - CPAPER
TI  - Binary Aggregation with Integrity Constraints
AU  - Grandi, Umberto
AU  - Endriss, Ulrich
T2  - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11
PB  - AAAI Press/International Joint Conferences on Artificial Intelligence
PY  - 2011
SP  - 204
EP  - 208
DO  - 10.5591/978-1-57735-516-8/IJCAI11-045
UR  - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-045
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