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Genetic programming theory and practice XX

Record Type:	Electronic resources : Monograph/item
Title/Author:	Genetic programming theory and practice XX/ edited by Stephan Winkler ... [et al.].
other author:	Winkler, Stephan.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xv, 337 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter 1. Symbolic Regression and Real World Applications -- Chapter 2. Program Synthesis with GP plus others -- Chapter 3. Machine learning and GP -- Chapter 4. Grammatical Evolution and Medical Applications of GP -- Chapter 5. Evolved Analytics LLC, Efficient Real-World Problem Solving with Genetic Programming -- Chapter 6. Automatic Machine Learning with GP -- Chapter 7. GP and Cybersecurity -- Transfer Learning and GP -- Chapter 8. Selection Mechanisms in Genetic Programming -- Chapter 9. Evolutionary Computation and Machine Learning.
Contained By:	Springer Nature eBook
Subject:	Genetic programming (Computer science) -
Online resource:	https://doi.org/10.1007/978-981-99-8413-8
ISBN:	9789819984138

Genetic programming theory and practice XX
Genetic programming theory and practice XX[electronic resource] /edited by Stephan Winkler ... [et al.]. - Singapore :Springer Nature Singapore :2024. - xv, 337 p. :ill. (some col.), digital ;24 cm. - Genetic and evolutionary computation,1932-0175. - Genetic and evolutionary computation..

Chapter 1. Symbolic Regression and Real World Applications -- Chapter 2. Program Synthesis with GP plus others -- Chapter 3. Machine learning and GP -- Chapter 4. Grammatical Evolution and Medical Applications of GP -- Chapter 5. Evolved Analytics LLC, Efficient Real-World Problem Solving with Genetic Programming -- Chapter 6. Automatic Machine Learning with GP -- Chapter 7. GP and Cybersecurity -- Transfer Learning and GP -- Chapter 8. Selection Mechanisms in Genetic Programming -- Chapter 9. Evolutionary Computation and Machine Learning.

Genetic Programming Theory and Practice 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.

ISBN: 9789819984138

Standard No.: 10.1007/978-981-99-8413-8doiSubjects--Topical Terms:

572479
Genetic programming (Computer science)

LC Class. No.: QA76.623

Dewey Class. No.: 006.3823

Genetic programming theory and practice XX
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245 0 0 $a Genetic programming theory and practice XX $h [electronic resource] / $c edited by Stephan Winkler ... [et al.].
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490 1 $a Genetic and evolutionary computation, $x 1932-0175
505 0 $a Chapter 1. Symbolic Regression and Real World Applications -- Chapter 2. Program Synthesis with GP plus others -- Chapter 3. Machine learning and GP -- Chapter 4. Grammatical Evolution and Medical Applications of GP -- Chapter 5. Evolved Analytics LLC, Efficient Real-World Problem Solving with Genetic Programming -- Chapter 6. Automatic Machine Learning with GP -- Chapter 7. GP and Cybersecurity -- Transfer Learning and GP -- Chapter 8. Selection Mechanisms in Genetic Programming -- Chapter 9. Evolutionary Computation and Machine Learning.
520 $a Genetic Programming Theory and Practice 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.
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