Automatically Evolving Lookup Tables for Function Approximation

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Automatically Evolving Lookup Tables for Function Approximation

Krauss, O; Langdon, WB; (2020) Automatically Evolving Lookup Tables for Function Approximation. In: Genetic Programming. EuroGP: European Conference on Genetic Programming (Part of EvoStar). (pp. pp. 84-100). Springer Nature Green open access

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Abstract

Many functions, such as square root, are approximated and sped up with lookup tables containing pre-calculated values. We introduce an approach using genetic algorithms to evolve such lookup tables for any smooth function. It provides double precision and calculates most values to the closest bit, and outperforms reference implementations in most cases with competitive run-time performance.

Type:	Proceedings paper
Title:	Automatically Evolving Lookup Tables for Function Approximation
Event:	EuroGP: 23rd European Conference on Genetic Programming (Part of EvoStar)
Location:	Seville, Spain
Dates:	15th-17th April 2020
ISBN-13:	978-3-030-44093-0
Open access status:	An open access version is available from UCL Discovery
DOI:	10.1007/978-3-030-44094-7_6
Publisher version:	https://doi.org/10.1007/978-3-030-44094-7_6
Language:	English
Additional information:	This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords:	Genetic Improvement, Objective function, Covariance matrix adaptation
UCL classification:	UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI:	https://discovery.ucl.ac.uk/id/eprint/10100133