March 19 – 24 , 2017, Dagstuhl Seminar 17121

Computational Complexity of Discrete Problems


Anna Gál (University of Texas – Austin, US)
Michal Koucký (Charles University – Prague, CZ)
Oded Regev (New York University, US)
Till Tantau (Universität zu Lübeck, DE)

For support, please contact

Dagstuhl Service Team


Dagstuhl Report, Volume 7, Issue 3 Dagstuhl Report
Aims & Scope
List of Participants
Dagstuhl's Impact: Documents available
Dagstuhl Seminar Schedule [pdf]


Introduction and goals

Computational complexity studies the amount of resources (such as time, space, randomness, or communication) that are necessary to solve computational problems in various models of computation. Finding efficient algorithms for solving computational tasks is crucial for practical applications and becomes even more important with the use of computers becoming part of everyday life. Despite a long line of research, for many problems that arise in practice it is not known if they can be solved efficiently - in particular in polynomial time.

Beside questions about the existence of polynomial time algorithms for problems like Satisfiability or Factoring where the best known algorithms run in exponential time, there is a huge class of practical problems where algorithms with polynomial running time (e.g. cubic or even quadratic time) are known, but it would be important to establish whether these running times are best possible, or to what extent they can be improved.

These fundamental questions motivate developments in various areas from algorithm design to circuit complexity, communication complexity and coding theory. During this Dagstuhl Seminar, we discussed some of the most exciting recent developments in those areas related to computational complexity.

The seminar "Computational Complexity of Discrete Problems" has evolved out of the series of seminars entitled "Complexity of Boolean Functions," a topic that has been covered at Dagstuhl on a regular basis since the foundation of this research center. An important feature of the current research in computational complexity is the integration of ideas from different subareas of computational complexity and from other fields in computer science and mathematics. We have aimed to attract researchers from various subareas connected to core questions in boolean function complexity and foster further fruitful interactions.

Summary text license
  Creative Commons BY 3.0 Unported license
  Anna Gál, Michal Koucký, Oded Regev, and Till Tantau

Dagstuhl Seminar Series


  • Data Structures / Algorithms / Complexity


  • Computational complexity
  • Discrete problems
  • Turing machines
  • Circuits
  • Communication complexity
  • Lower bounds
  • Upper bounds
  • Coding theory
  • Pseudorandomness
  • Derandomization
  • Hardness of approximation


In the series Dagstuhl Reports each Dagstuhl Seminar and Dagstuhl Perspectives Workshop is documented. The seminar organizers, in cooperation with the collector, prepare a report that includes contributions from the participants' talks together with a summary of the seminar.


Download overview leaflet (PDF).

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 on the ground floor of the library.


Furthermore, a comprehensive peer-reviewed collection of research papers can be published in the series Dagstuhl Follow-Ups.