Genetic Programming Theory and Practice XVII

ISBN-13: 9783030399603 / Angielski / Miękka / 2021 / 409 str.

Wolfgang Banzhaf; Erik Goodman; Leigh Sheneman

Spis treści

1. Characterizing the Effects of Random Subsampling on Lexicase Selection.- 2. It is Time for New Perspectives on How to Fight Bloatin GP.- 3. Explorations of the Semantic Learning Machine Neuroevolution Algorithm.- 4. Can Genetic Programming Perform Explainable Machine Learning for Bioinformatics?.- 5. Symbolic Regression by Exhaustive Search – Reducing the Search Space using Syntactical Constraints and Efficient Semantic Structure Deduplication.- 6. Temporal Memory Sharing in Visual Reinforcement Learning.- 7. The Evolution of Representations in Genetic Programming Trees.- 8. How Competitive is Genetic Programming in Business Data Science Applications?.- 9. Using Modularity Metrics as Design Features to Guide Evolution in Genetic Programming.- 10. Evolutionary Computation and AI Safety.- 11. Genetic Programming Symbolic Regression.- 12. Hands-on Artificial Evolution through Brain Programming.- 13. Comparison of Linear Genome Representations For Software Synthesis.- 14. Enhanced Optimization with Composite Objectives and Novelty Pulsation.- 15. New Pathways in Coevolutionary Computation.- 16. 2019 Evolutionary Algorithms Review.- 17. Evolving a Dota 2 Hero Bot with a Probabilistic Shared Memory Model.- 18. Modelling Genetic Programming as a Simple Sampling Algorithm.- 19.  An Evolutionary System for Better Automatic Software Repair.- Index.