Towards a General Boolean Function Benchmark Suite

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F23%3APU149636" target="_blank" >RIV/00216305:26230/23:PU149636 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1145/3583133.3590685" target="_blank" >http://dx.doi.org/10.1145/3583133.3590685</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3583133.3590685" target="_blank" >10.1145/3583133.3590685</a>

Result language

angličtina

Original language name

Towards a General Boolean Function Benchmark Suite

Original language description

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.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA22-02067S" target="_blank" >GA22-02067S: AppNeCo: Approximate Neurocomputing</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

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

ISBN

979-8-4007-0120-7

ISSN

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e-ISSN

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Number of pages

4

Pages from-to

591-594

Publisher name

Association for Computing Machinery

Place of publication

New York

Event location

Lisbon

Event date

Jul 15, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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