FUNCTION 2021, co-located with ICALP, is the first workshop focussing on “Flavors of UNCerTainty in Verification, Planning, and OpTimizatiON”.
We ask for presentations of ongoing or previously published work to enable discussions on a broad range of topics. These presentations will not be subject to proceedings publication. We encourage all interested speakers to submit an abstract of maximum 1 page via Easychair: https://easychair.org/conferences/?conf=function2021 ================== IMPORTANT DATES ================== Abstract submission: June 30, 2021 Notification: July 05, 2021 Workshop: July 11-12, 2021 ================== INVITED SPEAKERS ================== Rob Basten, Eindhoven University of Technology, NL Radu Calinescu, University of York, UK Rayna Dimitrova, CISPA Helmholtz Center for Information Security, DE Sebastian Junges, University of California, Berkeley, US Bruno Lacerda, University of Oxford, UK Morteza Lahijanian, University of Colorado Boulder, US Ahmadreza Marandi, Eindhoven University of Technology, NL Ransalu Senanayake, Stanford University, US Matthijs Spaan, Delft University of Technology, NL Wolfram Wiesemann, Imperial College London, UK ================== ORGANIZERS ================== Ernst Moritz Hahn, University of Twente, NL (e.m.h...@utwente.nl) Nils Jansen, Radboud University, Nijmegen, NL (n.jan...@science.ru.nl) Gethin Norman, University of Glasgow, UK (gethin.nor...@glasgow.ac.uk) ================== REGISTRATION ================== Registration is free by contacting the workshop organizers or through http://easyconferences.eu/icalp2021/registration/ Where workshop registration is free when registering for the ICALP conference and otherwise €10 until June 30 and €20 afterwards. ================== INFORMATION ================== https://function-2021.cs.ru.nl/ This interdisciplinary workshop aims at bringing together researchers from different areas that formally model and analyze systems under uncertainty. We aim to solicit presentations and discussions on aspects of uncertainty including: Epistemic vs Aleatoric Uncertainty, where there may be uncertainty on exact distributions in a system and solutions need to robustly account for such uncertainty; Parametric Uncertainty, where controllable system parameters are described by a function and solutions need to synthesize parameter values that satisfy given system specifications; Uncertainty that stems from statistical inference of distributions that are subject to confidence values and may take the form of interval Markov models; Uncertainty in the exact system state due to for example measurement errors or imprecise sensors, leading to partial or incorrect information. Such topics constitute active and relevant research in the areas including artificial intelligence, formal methods, operations research, and optimization. However, techniques and results have been obtained largely independently, and we expect strong synergy effects in sharing the specific yet often related views on uncertainty. — Dr. Nils Jansen Assistant Professor Department of Software Science Radboud University Nijmegen http://nilsjansen.org _______________________________________________ uai mailing list uai@engr.orst.edu https://it.engineering.oregonstate.edu/mailman/listinfo/uai
