
This volume contains the Short Paper Proceedings of the 21st International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2026, held on June 15-19, 2026, at the Faculty of Economics of Sapienza University of Rome, Rome, Italy. The IPMU conference is organized every two years. It aims to bring together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, the IPMU conference has provided a forum for exchanging ideas between theoreticians and practitioners working in these areas and related fields. The 2026 edition of IPMU celebrated the 40th anniversary of the first edition of the conference that took place in Paris, France. Rome was a particular fitting choice for this special occasion, as Rome and Paris have been exclusively and reciprocally twinned since April 1956. For IPMU 2026, the authors had the option of submitting either regular papers or short papers. The present volume contains 51 of the accepted short papers. All accepted papers underwent a thorough review process and were evaluated by at least two reviewers. Furthermore, all papers were examined by the program chairs. The reviewing process respected the usual conflict-of-interest standards, so that all papers received multiple independent evaluations.
Information aggregation, Uncertainty management, Intelligent Systems
Information aggregation, Uncertainty management, Intelligent Systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
