Parameterized complexity and the search for tight complexity results

Objective

The joint goal of theoretical research in algorithms and
computational complexity is to discover all the relevant algorithmic techniques
in a problem domain and prove the optimality of these techniques.
We propose that the search for such tight results should be done
by a combined exploration of the dimensions running time, quality
of solution, and generality. Furthermore, the theory of parameterized complexity
provides a framework for this exploration.

Parameterized complexity is a theory whose goal is to
produce efficient algorithms for hard combinatorial problems using
a multi-dimensional analysis of the running time. Instead of
expressing the running time as a function of the input size only
(as it is done in classical complexity theory), parameterized
complexity tries to find algorithms whose running time is
polynomial in the input size, but exponential in one or more
well-defined parameters of the input instance.

The first objective of the project is to go beyond the
state of the art in the complexity and algorithmic aspects of
parameterized complexity in order to turn it into a theory
producing tight optimality results. With such theory at hand, we
can start the exploration of other dimensions and obtain tight
optimality results in a larger context. Our is goal is being able
to prove in a wide range of settings that we understand all the
algorithmic ideas and their optimality.

Funding Scheme

ERC-SG - ERC Starting Grant

Host institution

SZAMITASTECHNIKAI ES AUTOMATIZALASI KUTATOINTEZET

EU contribution

€ 1 150 000,00

Address

KENDE UTCA 13-17
1111 Budapest
Hungary

Region

Közép-Magyarország Budapest Budapest

Activity type

Research Organisations

Principal investigator

Dániel Marx (Dr.)

Administrative Contact

Andras Benczur (Dr.)

Links

Contact the organisation Website

Total cost

No data

Beneficiaries (1)