Highlights of Semantics in Multi-objective Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7642

@InProceedings{Galvan-Lopez:2022:GECCOhop,

• author = "Edgar Galvan and Leonardo Trujillo and Fergal Stapleton",
• title = "Highlights of Semantics in Multi-objective Genetic Programming",
• booktitle = "Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion",
• year = "2022",
• editor = "Marcus Gallagher",
• pages = "19--20",
• address = "Boston, USA",
• series = "GECCO '22",
• month = "9-13 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, diversity, semantics, multi-objective genetic programming",
• isbn13 = "978-1-4503-9268-6/22/07",
• DOI = "doi:10.1145/3520304.3534073",
• video_url = "https://vimeo.com/723511007",
• abstract = "Semantics is a growing area of research in Genetic programming (GP) and refers to the behavioural output of a Genetic Programming individual when executed. This research expands upon the current understanding of semantics by proposing a new approach: Semantic-based Distance as an additional criteriOn (SDO), in the thus far, somewhat limited researched area of semantics in Multi-objective GP (MOGP). Our work included an expansive analysis of the GP in terms of performance and diversity metrics, using two additional semantic-based approaches, namely Semantic Similarity-based Crossover (SCC) and Semantic-based Crowding Distance (SCD). Each approach is integrated into two evolutionary multi-objective (EMO) frameworks: Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2), and along with the three semantic approaches, the canonical form of NSGA-II and SPEA2 are rigorously compared. Using highly-unbalanced binary classification datasets, we demonstrated that the newly proposed approach of SDO consistently generated more non-dominated solutions, with better diversity and improved hypervolume results.This Hot-off-the-Press paper summarises {"}Semantics in Multi-objective Genetic Programming{"} by Edgar Galv\'{a}n, Leonardo Trujillo and Fergal Stapleton, published in the journal of Applied Soft Computing 2022 [9], https://doi.org/10.1016/j.asoc.2021.108143.",
• notes = "GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Edgar Galvan Lopez Leonardo Trujillo Fergal Stapleton

Citations