Genetic Programming Theory and Practice XX / edited by Stephan Winkler, Leonardo Trujillo, Charles Ofria, Ting Hu.

Format:

Book

Contributor:

Winkler, Stephan, editor.

Series:

Genetic and Evolutionary Computation, 1932-0175

Language:

English

Subjects (All):

Artificial intelligence.

Artificial Intelligence.

Local Subjects:

Artificial Intelligence.

Physical Description:

1 online resource (343 pages)

Edition:

1st ed. 2024.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2024.

Summary:

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.

Contents:

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.

Notes:

Includes bibliographical references and index.

ISBN:

981-9984-13-0