Publication result detail

TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming

KALKREUTH, R.; DE, O.; JANKOVIC, A.; ANASTACIO, M.; DIERKES, J.; VAŠÍČEK, Z.; HOOS, H.

Original Title

TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming

English Title

TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

Over the years, genetic programming (GP) has evolved, with many proposed variations, especially in how they represent a solution. Being essentially a program synthesis algorithm, it is capable of tackling multiple problem domains. Current benchmarking initiatives are fragmented, as the different representations are not compared with each other and their performance is not measured across the different domains. In this work, we propose a unified framework, dubbed TinyverseGP (inspired by tinyGP), which provides support to multiple representations and problem domains, including symbolic regression, logic synthesis and policy search.

English abstract

Over the years, genetic programming (GP) has evolved, with many proposed variations, especially in how they represent a solution. Being essentially a program synthesis algorithm, it is capable of tackling multiple problem domains. Current benchmarking initiatives are fragmented, as the different representations are not compared with each other and their performance is not measured across the different domains. In this work, we propose a unified framework, dubbed TinyverseGP (inspired by tinyGP), which provides support to multiple representations and problem domains, including symbolic regression, logic synthesis and policy search.

Keywords

Genetic Programming, Implementation, Benchmarking, Symbolic Regression, Logic Synthesis, Python

Key words in English

Genetic Programming, Implementation, Benchmarking, Symbolic Regression, Logic Synthesis, Python

Authors

KALKREUTH, R.; DE, O.; JANKOVIC, A.; ANASTACIO, M.; DIERKES, J.; VAŠÍČEK, Z.; HOOS, H.

Released

14.07.2025

Publisher

Association for Computing Machinery

Location

Malaga

ISBN

979-8-4007-1464-1

Book

Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages from

2172

Pages to

2176

Pages count

5

BibTex

@inproceedings{BUT197539,
  author="KALKREUTH, R. and DE, O. and JANKOVIC, A. and ANASTACIO, M. and DIERKES, J. and VAŠÍČEK, Z. and HOOS, H.",
  title="TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming",
  booktitle="Proceedings of the Genetic and Evolutionary Computation Conference Companion",
  year="2025",
  pages="2172--2176",
  publisher="Association for Computing Machinery",
  address="Malaga",
  doi="10.1145/3712255.3726697",
  isbn="979-8-4007-1464-1"
}