Evolutionary Algorithms for Segment Optimization in Vectorial GP [Poster]

Philipp Fleck, Stephan Winkler, Michael Kommenda, Sara Silva, Leonardo Vanneschi, Michael Affenzeller

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Vectorial Genetic Programming (Vec-GP) extends regular GP by allowing vectorial input features (e.g. time series data), while retaining the expressiveness and interpretability of regular GP. The availability of raw vectorial data during training, not only enables Vec-GP to select appropriate aggregation functions itself, but also allows Vec-GP to extract segments from vectors prior to aggregation (like windows for time series data). This is a critical factor in many machine learning applications, as vectors can be very long and only small segments may be relevant. However, allowing aggregation over segments within GP models makes the training more complicated. We explore the use of common evolutionary algorithms to help GP identify appropriate segments, which we analyze using a simplified problem that focuses on optimizing aggregation segments on fixed data. Since the studied algorithms are to be used in GP for local optimization (e.g. as mutation operator), we evaluate not only the quality of the solutions, but also take into account the convergence speed and anytime performance. Among the evaluated algorithms, CMA-ES, PSO and ALPS show the most promising results, which would be prime candidates for evaluation within GP.
Original languageEnglish
Title of host publicationGECCO '23 Companion
Subtitle of host publicationProceedings of the Companion Conference on Genetic and Evolutionary Computation
EditorsSara Silva, Luís Paquete
Place of PublicationNew York
PublisherACM - Association for Computing Machinery
Number of pages4
ISBN (Print)9798400701207
Publication statusPublished - 24 Jul 2023
EventThe Genetic and Evolutionary Computation Conference (GECCO 2023) - Lisbon, Portugal
Duration: 15 Jul 202319 Jul 2023
Conference number: 2023


ConferenceThe Genetic and Evolutionary Computation Conference (GECCO 2023)
Abbreviated titleGECCO 2023
Internet address


  • evolutionary algorithms regression, genetic programming, vectorial
  • symbolic regression
  • genetic programming
  • vectorial


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