Genetic Programming Theory and Practice XXI

Chapter 1. Representation & Reachability: Assumption Impact in Data Modeling.- Chapter 2. EvoFeat: Genetic Programming-based Feature Engineering Approach to Tabular Data Classification.- Chapter 3.  Deep Learning-Based Operators for Evolutionary Algorithms.- Chapter 4.  Survey of Genetic Programming and Large Language Models.- Chapter 5.  Evolving Many-Model Agents with Vector and Matrix Operations in Tangled Program Graphs.- Chapter 6.  Automatic Design of Autoencoders using NeuroEvolution.- Chapter 7. Code Building Genetic Programming is Faster than PushGP.- Chapter 8. Sharpness-Aware Minimization in Genetic Programming.- Chapter 9. Tree-Based Grammatical Evolution with Non-Encoding Nodes.- Chapter 10.  Genetic Programming with Memory for Approximate Data Reconstruction.- Chapter 11.  Ratcheted Random Search for Self-Programming Boolean Networks.- Chapter 12.  Exploring Non-Bloating Geometric Semantic Genetic Programming.- Chapter 13. Revisiting Gradient-based Local Search in Symbolic Regression.- Chapter 14. It’s Time to Revisit the Use of FPGAs for Genetic Programming.- Chapter 15. Interpretable Genetic Programming Models for Real-World
Biomedical Images.- Chapter 16. Crafting Generative Art through Genetic Improvement: Managing Creative Outputs in Diverse Fitness Landscapes.- Chapter 17.  Cell Regulation and the Early Evolution of Autonomous Control.- Chapter 18.  How to Measure Explainability and Interpretability of Machine Learning Results.- Chapter 19.  Lexicase Selection Parameter Analysis: Varying Population Size and Test Case Redundancy with Diagnostic Metrics.- Chapter 20.  Using lineage age to augment search space exploration in lexicase selection.

• Erscheinungsdatum: 27.02.2025
• Autor/Autorin: Stephan M. Winkler
• Reihe: Artificial Intelligence (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 30.6 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 300 Seiten
• ISBN: 9789819600779
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