Publication Details
Towards a General Boolean Function Benchmark Suite
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY)
Husa Jakub, Ing. (DCSY)
VERMETTEN, D.
YE, F.
THOMAS, B.
Benchmarking, Boolean function learning, Genetic Programming
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.
@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"
}