References

  1. A. Barbu & N. Lay (2012): An Introduction to Artificial Prediction Markets for Classification. Journal of Machine Learning Research 13, pp. 2177–2204. Available at http://dl.acm.org/citation.cfm?id=2503312.
  2. G. Boella, G. Pigozzi, M. Slavkovik & L. van der Torre (2011): Group Intention Is Social Choice with Commitment. In: M. De Vos, N. Fornara, J. Pitt & G. Vouros: COIN in Agent Systems VI, LNCS 6541. Springer, Germany, pp. 152–171, doi:10.1007/978-3-642-21268-0_9.
  3. I. Bozbay (2019): Truth-tracking Judgment Aggregation over Interconnected Issues. Social Choice and Welfare, pp. 1–34, doi:10.1007/s00355-019-01186-6.
  4. M.M. Deza & E. Deza (2009): Encyclopedia of Distances. Springer, Germany, doi:10.1007/978-3-642-00234-2.
  5. F. Dietrich (2007): A Generalized Model of Judgment Aggregation. Social Choice and Welfare 28(4), pp. 529–565, doi:10.1007/s00355-006-0187-y.
  6. F. Dietrich (2014): Scoring Rules for Judgment Aggregation. Social Choice and Welfare 42(4), pp. 873–911, doi:10.1007/s00355-013-0757-8.
  7. F. Dietrich & C. List (2010): The Aggregation of Propositional Attitudes: Towards a General Theory. Oxford Studies in Epistemology 3, pp. 215–234. Available at http://eprints.lse.ac.uk/id/eprint/31600.
  8. F. Dietrich & C. List (2017): Probabilistic Opinion Pooling Generalized. Part one: General Agendas. Social Choice and Welfare 48(4), pp. 747–786, doi:10.1007/s00355-017-1034-z.
  9. F. Dietrich & C. List (2018): From Degrees of Belief to Binary Beliefs: Lessons from Judgment-aggregation Theory. The Journal of Philosophy 115, pp. 225–270, doi:10.5840/jphil2018115516.
  10. F. Dietrich & P. Mongin (2010): The Premisse-Based Approach to Judgment Aggregation. Journal of Economic Theory 145(2), pp. 562–582, doi:10.1016/j.jet.2010.01.011.
  11. E. Dokow & R. Holzman (2010): Aggregation of Binary Evaluations with Abstentions. Journal of Economic Theory 145(2), pp. 544 – 561, doi:10.1016/j.jet.2009.10.015.
  12. D. Dubois & H. Prade (2001): Possibility Theory in Information Fusion. In: G. Della Riccia, H.J. Lenz & R. Kruse: Data Fusion and Perception. Springer Vienna, Vienna, pp. 53–76, doi:10.1007/978-3-7091-2580-9_3.
  13. U. Endriss (2018): Judgment Aggregation with Rationality and Feasibility Constraints. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS '18. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, pp. 946–954. Available at http://dl.acm.org/citation.cfm?id=3237383.3237840.
  14. U. Endriss, U. Grandi, R. de Haan & J. Lang (2016): Succinctness of Languages for Judgment Aggregation. In: Proceedings of KR-2016. AAAI Press, USA, pp. 176–186. Available at http://www.aaai.org/ocs/index.php/KR/KR16/paper/view/12851.
  15. U. Endriss & R. de Haan (2015): Complexity of the Winner Determination Problem in Judgment Aggregation: Kemeny, Slater, Tideman, Young. In: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS '15. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, pp. 117–125. Available at http://dl.acm.org/citation.cfm?id=2772879.2772897.
  16. P. Everaere, S. Konieczny & P. Marquis (2014): Counting votes for aggregating judgments. In: International conference on Autonomous Agents and Multi-Agent Systems, AAMAS '14, Paris, France, May 5-9, 2014, pp. 1177–1184. Available at http://dl.acm.org/citation.cfm?id=2617436.
  17. P. Everaere, S. Konieczny & P. Marquis (2015): Belief Merging versus Judgment Aggregation. In: Proceedings of the AAMAS-2015, pp. 999–1007. Available at http://dl.acm.org/citation.cfm?id=2773279.
  18. R. Fagin, J. Y. Halpern & N. Megiddo (1990): A Logic for Reasoning about Probabilities. Information and Computation 87, pp. 78–128, doi:10.1016/0890-5401(90)90060-U.
  19. D. Grossi & G. Pigozzi (2014): Judgment Aggregation: A Primer. Morgan and Claypool Publishers, San Rafael, CA, USA, doi:10.2200/S00559ED1V01Y201312AIM027.
  20. J. Y. Halpern (2005): Reasoning about uncertainty. MIT Press. Available at https://mitpress.mit.edu/books/reasoning-about-uncertainty-second-edition.
  21. M. Ivanovska & M. Giese (2010): Probabilistic Logic with Conditional Independence Formulae. In: Proceedings of ECAI 2010 - 19th European Conference on Artificial Intelligence, pp. 983–984, doi:10.3233/978-1-60750-606-5-983.
  22. A. Jøsang (2016): Subjective Logic: A Formalism for Reasoning Under Uncertainty. Artificial Intelligence: Foundations, Theory, and Algorithms. Springer International Publishing, doi:10.1007/978-3-319-42337-1.
  23. J. Lang & M. Slavkovik (2013): Judgment Aggregation Rules and Voting Rules. In: Proceedings of the 3rd International Conference on Algorithmic Decision Theory, Lecture Notes in Artificial Intelligence 8176. Springer-Verlag, Germany, pp. 230–244, doi:10.1007/978-3-642-41575-3_18.
  24. J. Lang & M. Slavkovik (2014): How Hard is it to Compute Majority-Preserving Judgment Aggregation Rules?. In: Proceedings of ECAI-2014, Frontiers in Artificial Intelligence and Applications 263:ECAI 2014. IOS Press, Netherlands, pp. 501–506, doi:10.3233/978-1-61499-419-0-501.
  25. J. Lang, M. Slavkovik & S. Vesic (2016): Agenda Separability in Judgment Aggregation. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), pp. 1016–1022. Available at http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12084.
  26. L. Lang, P. Pigozzi, M. Slavkovik, L. van der Torre & S. Vesic (2016): A partial taxonomy of judgment aggregation rules, and their properties. Social Choice and Welfare 48, pp. 1–30, doi:10.1007/s00355-016-1006-8.
  27. C. List & C. Puppe (2009): Judgment aggregation: A survey. In: P. Anand, C. Puppe & P. Pattanaik: The Handbook of Rational and Social Choice. Oxford University Press, UK, doi:10.1093/acprof:oso/9780199290420.003.0020.
  28. C. Martini & J Sprenger (2017): Opinion Aggregation and Individual Expertise.. In: Scientific Collaboration and Collective Knowledge: New Essays. Oxford Scholarship, UK, doi:10.1093/oso/9780190680534.001.0001.
  29. S. Moral & J. Del Sagrado (1998): Aggregation of Imprecise Probabilities. In: Aggregation and fusion of imperfect information. Springer, Germany, pp. 162–188, doi:10.1007/978-3-7908-1889-5_10.
  30. K. Nehring & M. Pivato (2013): Majority Rule in the Absence of a Majority. MPRA Paper 46721. University Library of Munich, Germany, doi:10.1016/j.jet.2019.05.006.
  31. G. Pigozzi, M. Slavkovik & L. van der Torre (2009): A Complete Conclusion-Based Procedure for Judgment Aggregation. In: F. Rossi & A. Tsoukias: Algorithmic Decision Theory, Lecture Notes in Computer Science 5783. Springer, Berlin Heidelberg, pp. 1–13, doi:10.1007/978-3-642-04428-1_1.
  32. N. Potyka, E. Acar, M. Thimm & H. Stuckenschmidt (2016): Group Decision Making via Probabilistic Belief Merging. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI'16. AAAI Press, pp. 3623–3629. Available at http://dl.acm.org/citation.cfm?id=3061053.3061126.
  33. N. Potyka & M. Thimm (2017): Inconsistency-tolerant Reasoning over Linear Probabilistic Knowledge Bases. International Journal of Approximate Reasoning 88, pp. 209 – 236, doi:10.1016/j.ijar.2017.06.002.
  34. M. Slavkovik (2012): Judgment Aggregation for Multiagent Systems. Doctoral Thesis, University of Luxembourg. Uitgeverij BOXPress, Netherlands. Available at http://icr.uni.lu/Marija/thesis.pdf.
  35. M. Slavkovik & T. Ågotnes (2014): Measuring Dissimilarity between Judgment Sets. In: Logics in Artificial Intelligence, Lecture Notes in Computer Science 8761. Springer International Publishing, pp. 609–617, doi:10.1007/978-3-319-11558-0_44.
  36. M. Slavkovik & G. Boella (2012): Recognition-primed group decisions via judgement aggregation. Synthese 189(1), pp. 51–65, doi:10.1007/s11229-012-0161-4.
  37. R. T. Stewart & I. O. Quintana (2018): Probabilistic Opinion Pooling with Imprecise Probabilities. Journal of Philosophical Logic 47(1), pp. 17–45, doi:10.1007/s10992-016-9415-9.
  38. T. Strzemecki (1992): Polynomial-time Algorithms for Generation of Prime Implicants. Journal of Complexity 8(1), pp. 37 – 63, doi:10.1016/0885-064X(92)90033-8.
  39. Z. Terzopoulou, U. Endriss & R. de Haan (2018): Aggregating Incomplete Judgments: Axiomatisations for Scoring Rules. In: Proceedings of the COMSOC-2018. online. Available at http://research.illc.uva.nl/COMSOC/proceedings/comsoc-2018/TerzopoulouEtAlCOMSOC2018.pdf.
  40. C. Wagner (1984): Aggregating Subjective Probabilities: Some Limitative Theorems. Notre Dame Journal of Formal Logic 25, pp. 233–240, doi:10.1305/ndjfl/1093870630.
  41. J. Wolfers & E. Zitzevitz (2004): Prediction Markets. Journal of Economic Perspectives 18(2), pp. 107–126, doi:10.1257/0895330041371321.

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