Genetic Programming Theory and Practice XVIII 1st Edition by Wolfgang Banzhaf 9783030399580 3030399583

Genetic Programming Theory and Practice XVIII 1st Edition Wolfgang Banzhaf – Ebook Instant Download/Delivery ISBN(s): 9789811681127,9811681120, 9783030399580, 3030399583

Product details:

• ISBN 10: 3030399583
• ISBN 13: 9783030399580
• Author: Wolfgang Banzhaf

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP.  In this year’s edition, the topics covered include many of the most important issues and research questions in the field, such as: opportune application domains for GP-based methods, game playing and co-evolutionary search, symbolic regression and efficient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms.The volume includes several chapters on best practices and lessons learned from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.

Table contents:

1. Characterizing the Effects of Random Subsampling on Lexicase Selection
2. It Is Time for New Perspectives on How to Fight Bloat in GP
3. Explorations of the Semantic Learning Machine Neuroevolution Algorithm: Dynamic Training Data Use, Ensemble Construction Methods, and Deep Learning Perspectives
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: What Is the Prior on the Prediction?
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

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