Detail publikace

Towards a General Boolean Function Benchmark Suite

KALKREUTH, R. VAŠÍČEK, Z. HUSA, J. VERMETTEN, D. YE, F. THOMAS, B.

Originální název

Towards a General Boolean Function Benchmark Suite

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Just over a decade ago, the first comprehensive review on the state of benchmarking in Genetic Programming (GP) analyzed the mismatch between the problems that are used to test the performance of GP systems and real-world problems. Since then, several benchmark suites in major GP problem domains have been proposed over time, which were able to fill some of the major gaps. In the framework of the first review about the state of benchmarking in GP, logic synthesis was classified as one of the major GP problem domains. However, a diverse and accessible benchmark suite for logic synthesis is still missing in the field of GP. In this work, we take a first step towards a benchmark suite for logic synthesis that covers different types of Boolean functions that are commonly used for the evaluation of GP systems. We also present baseline results that have been obtained by former work and in our evaluation experiments by using Cartesian Genetic Programming.

Klíčová slova

Benchmarking, Boolean function learning, Genetic Programming 

Autoři

KALKREUTH, R.; VAŠÍČEK, Z.; HUSA, J.; VERMETTEN, D.; YE, F.; THOMAS, B.

Vydáno

15. 7. 2023

Nakladatel

Association for Computing Machinery

Místo

New York

ISBN

979-8-4007-0120-7

Kniha

GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

Strany od

591

Strany do

594

Strany počet

4

BibTex

@inproceedings{BUT185458,
  author="KALKREUTH, R. and VAŠÍČEK, Z. and HUSA, J. and VERMETTEN, D. and YE, F. and THOMAS, B.",
  title="Towards a General Boolean Function Benchmark Suite",
  booktitle="GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion",
  year="2023",
  pages="591--594",
  publisher="Association for Computing Machinery",
  address="New York",
  doi="10.1145/3583133.3590685",
  isbn="979-8-4007-0120-7"
}