Genetic Programming Theory and Practice XIX

Leonardo Trujillo

ISBN 10: 981198462X / ISBN 13: 9789811984624

Verlag: Springer Nature Singapore, 2024

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research.

Bestandsnummer des Verkäufers 9789811984624

Bibliografische Details

• Titel: Genetic Programming Theory and Practice XIX
• Verlag: Springer Nature Singapore
• Erscheinungsjahr: 2024
• Sprache: Englisch
• ISBN-10: 981198462X
• ISBN-13: 9789811984624
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 16 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 16 mm
• Gewicht: 423 Gramm

Über diesen Titel

Inhaltsangabe

This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm.

Von der hinteren Coverseite

This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year´s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research.