https://www.dagstuhl.de/21255

June 20 – 23 , 2021, Event 21255

Workshop des GRK UnRAVeL

Organizer

Joost-Pieter Katoen (RWTH Aachen, DE)

For support, please contact

Heike Clemens

Description

Uncertainty is nowadays more and more pervasive in computer science. It is important both in big data and at the level of events and control. Applications have to treat large amounts of data, often from unreliable sources such as noisy sensors and untrusted web pages. Data may also be subject to continuous changes, may come in different formats, and is often incomplete. Robots, trains, and production machines have to deal with unpredictable environments. The growing use of machine-learning components — often providing weak guarantees — forms an additional factor of uncertainty.

The aim of this RTG is to significantly advance various theoretical concepts (in algorithms, logic, verification) as well as their connection to deal with uncertainty and randomness, and to tailor and apply these techniques to problems in application areas such as railway engineering, network dynamics, and cyber-physical systems

Motivation text license
  Creative Commons BY 3.0 DE
  Joost-Pieter Katoen

Classification

  • Cs.AI - Artificial Intelligence
  • Cs.DB - Databases
  • Cs.FL - Format Languages And Automata Theory
  • Cs.LO - Logic In Computer Science
  • Cs.PL - Programming Languages

Online Publications

We offer several possibilities to publish the results of your event. Please contact publishing(at)dagstuhl.de if you are interested.

Dagstuhl's Impact

Please inform us when a publication was published as a result from your seminar. These publications are listed in the category Dagstuhl's Impact and are presented on a special shelf in the library.