Genetic Programming Theory and Practice XIX

Leonardo Trujillo, Stephan M. Winkler, Sara Silva, Wolfgang Banzhaf (Herausgeber)

Buch | Softcover

262 Seiten

2024 | 2023 ed.
Springer Verlag, Singapore
978-981-19-8462-4 (ISBN)

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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.

Chapter 1. Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data.- Chapter 2. Correlation versus RMSE Loss Functions in Symbolic Regression Tasks.- Chapter 3. GUI-Based, Efficient Genetic Programming and AI Planning For Unity3D.- Chapter 4. Genetic Programming for Interpretable and Explainable Machine Learning.- Chapter 5. Biological Strategies ParetoGP Enables Analysis of Wide and Ill-Conditioned Data from Nonlinear Systems.- Chapter 6. GP-Based Generative Adversarial Models.- Chapter 7. Modelling Hierarchical Architectures with Genetic Programming and Neuroscience Knowledge for Image Classification through InferentialKnowledge.- Chapter 8. Life as a Cyber-Bio-Physical System.- Chapter 9. STREAMLINE: A Simple, Transparent, End-To-End Automated Machine Learning Pipeline Facilitating Data Analysis and Algorithm Comparison.- Chapter 10. Evolving Complexity is Hard.- Chapter 11. ESSAY: Computers Are Useless ... They Only Give Us Answers.

Erscheinungsdatum	12.03.2024
Reihe/Serie	Genetic and Evolutionary Computation
Zusatzinfo	93 Illustrations, color; 11 Illustrations, black and white; XIV, 262 p. 104 illus., 93 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Theorie / Studium ► Algorithmen
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie
	Technik ► Medizintechnik
Schlagworte	Artificial Evolution • Automatic Modelling • evolutionary machine learning • Genetic improvement • genetic programming • Genetic Programming Applications • Genetic Programming Theory • Lexicase selection • Model Discovery • Program Synthesis • Symbolic Regression
ISBN-10	981-19-8462-X / 981198462X
ISBN-13	978-981-19-8462-4 / 9789811984624
Zustand	Neuware