ESAGP – A semantic GP framework based on alignment in the error space

Stefano Ruberto, Leonardo Vanneschi, Mauro Castelli, Sara Silva

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Citations (Scopus)


This paper introduces the concepts of error vector and error space, directly bound to semantics, one of the hottest topics in genetic programming. Based on these concepts, we introduce the notions of optimally aligned individuals and optimally coplanar individuals. We show that, given optimally aligned, or optimally coplanar, individuals, it is possible to construct a globally optimal solution analytically. Thus, we introduce a genetic programming framework for symbolic regression called Error Space Alignment GP (ESAGP) and two of its instances: ESAGP-1, whose objective is to find optimally aligned individuals, and ESAGP-2, whose objective is to find optimally coplanar individuals. We also discuss how to generalize the approach to any number of dimensions. Using two complex real-life applications, we provide experimental evidence that ESAGP-2 outperforms ESAGP-1, which in turn outperforms both standard GP and geometric semantic GP. This suggests that “adding dimensions” is beneficial and encourages us to pursue the study in many different directions, that we summarize in the final part of the manuscript.

Original languageEnglish
Title of host publicationGenetic Programming - 17th European Conference, EuroGP 2014, Revised Selected Papers
EditorsPablo García-Sánchez, Juan J. Merelo, Victor M. Rivas Santos, Miguel Nicolau, Krzysztof Krawiec, Malcolm I. Heywood, Mauro Castelli, Kevin Sim
PublisherSpringer Verlag
Number of pages12
ISBN (Electronic)9783662443026
Publication statusPublished - 1 Jan 2014
Event17th European Conference on Genetic Programming, EuroGP 2014 - Granada, Spain
Duration: 23 Apr 201425 Apr 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th European Conference on Genetic Programming, EuroGP 2014


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