Genetic Programming Theory and Practice XIX

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.

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• Análise numérica
• Algoritmos e estruturas de dados
• Aprendizagem mecânica
• Engenharia biomédica

Genetic Programming;Genetic Programming Theory;Genetic Programming Applications;Symbolic Regression;Evolutionary Machine Learning;Program Synthesis;Genetic Improvement;Lexicase Selection;Artificial Evolution;Model Discovery;Automatic Modelling