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Genetic programming28th European Conference, EuroGP 2025, held as part of EvoStar 2025, Trieste, Italy, April 23-25, 2025 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Genetic programmingedited by Bing Xue, Luca Manzoni, Illya Bakurov.
Reminder of title:	28th European Conference, EuroGP 2025, held as part of EvoStar 2025, Trieste, Italy, April 23-25, 2025 : proceedings /
remainder title:	EuroGP 2025
other author:	Xue, Bing.
corporate name:
Published:	Cham :Springer Nature Switzerland :2025.
Description:	x, 258 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Genetic programming (Computer science)
Online resource:	https://doi.org/10.1007/978-3-031-89991-1
ISBN:	9783031899911$q(electronic bk.)

Genetic programming28th European Conference, EuroGP 2025, held as part of EvoStar 2025, Trieste, Italy, April 23-25, 2025 : proceedings /
Genetic programming28th European Conference, EuroGP 2025, held as part of EvoStar 2025, Trieste, Italy, April 23-25, 2025 : proceedings /[electronic resource] :EuroGP 2025edited by Bing Xue, Luca Manzoni, Illya Bakurov. - Cham :Springer Nature Switzerland :2025. - x, 258 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,156091611-3349 ;. - Lecture notes in computer science ;4891..

Ghost Swarms: Learning Swarm Rules from Environmental Changes Alone. -- A Systematic Evaluation of Evolving Highly Nonlinear Boolean Functions in Odd Sizes. -- Exploring the Impact of Data Scale on Mutation Step Size in SLIM-GSGP. -- Multi-Objective Evolutionary Design of Explainable EEG Classifier. -- On the Effectiveness of Crossover Operators in Cartesian Genetic Programming. -- Population Diversity, Information Theory and Genetic Improvement. -- Introducing Crossover in SLIM-GSGP. -- Exploring the Integration of Cellular Structures in Genetic Programming-based Methods. -- Ant-based Metaheuristics Struggle to Solve the Cartesian Genetic Programming Learning Task. -- Designing Lookahead Relocation Rules for the Container Relocation Problem with Genetic Programming. -- Evolved and Transparent Pipelines for Biomedical Image Classification. -- Unified Piecewise Symbolic Regression. -- Was Tournament Selection All We Ever Needed? A Critical Reflection on Lexicase Selection. -- The Role of Stepping Stones in MAP-Elites: Insights from Search Trajectory Networks. -- Micro-Step Time-Series Regression: Insights from System Identification Using Symbolic Regression.

This book constitutes the refereed proceedings of the 28th European Conference on Genetic Programming, EuroGP 2025, held in Trieste, Italy, during April 23-25, 2025 and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EvoApplications. The 10 full papers were and 5 short papers included in this volume were carefully reviewed and selected from 27 submissions.The wide range of topics in this volume reflects the current state of research in the field. The universality of computer programs and their importance in so many areas of our lives means that automating these tasks is an exceptionally ambitious challengewith far-reaching implications.

ISBN: 9783031899911$q(electronic bk.)

Standard No.: 10.1007/978-3-031-89991-1doiSubjects--Topical Terms:

206263
Genetic programming (Computer science)

LC Class. No.: QA76.623 / .E94 2025

Dewey Class. No.: 006.31

Genetic programming28th European Conference, EuroGP 2025, held as part of EvoStar 2025, Trieste, Italy, April 23-25, 2025 : proceedings /
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520 $a This book constitutes the refereed proceedings of the 28th European Conference on Genetic Programming, EuroGP 2025, held in Trieste, Italy, during April 23-25, 2025 and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EvoApplications. The 10 full papers were and 5 short papers included in this volume were carefully reviewed and selected from 27 submissions.The wide range of topics in this volume reflects the current state of research in the field. The universality of computer programs and their importance in so many areas of our lives means that automating these tasks is an exceptionally ambitious challengewith far-reaching implications.
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