Genetic programming theory and practice IX

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. Topics include: modularity and scalability; evolvability; human-competitive results; the need for important high-impact GP-solvable problems;; the risks of search stagnation and of cutting off paths tosolutions; the need for novelty; empowering GP search with expert knowledge; In addition, GP symbolic regression is thoroughly discussed, addressing such topics as guaranteed reproducibility of SR; validating SR results, measuring and controlling genotypic complexity; controlling phenotypic complexity; identifying, monitoring, and avoiding over-fitting; finding a comprehensive collection of SR benchmarks, comparing SR to machine learning. This text is for all GP explorers. Readers will discover large-scale, real-world applications of GP toa variety of problem domains via in-depth presentations of the latest and most significant results. Describes cutting-edge work on genetic programming (GP) theory, applications of GP, and how theory can be used to guide application of GP Demonstrates large-scale applications of GP to a variety of problem domains. Reveals an inspiring synergy between GP applications and the latest in theoretical results for state-of - the-art problem solving. Addresses symbolic regression as a mode of genetic programming. INDICE: What’s in an evolved name? The evolution of modularity via tag-based Reference. Let the Games Evolve!. Novelty Search and the Problem with Objectives. A fine-grained view of phenotypes and locality in genetic programming. Evolution of an Effective Brain-Computer Interface Mouse via Genetic Programming with Adaptive Tarpeian Bloat Control. Improved Time Series Prediction and Symbolic Regression with Affine Arithmetic. Computational Complexity Analysis of Genetic Programming - Initial Results and Future Directions. Accuracy in Symbolic Regression. Human-Computer Interaction in a Computational Evolution System for the Genetic Analysis of Cancer. Baseline Genetic Programming: Symbolic Regression on Benchmarks for Sensory Evaluation Modeling. Detecting Shadow Economy Sizes With Symbolic Regression. The Importance of Being Flat - Studying the Program Length Distributions of Operator Equalisation. FFX: Fast, Scalable,Deterministic Symbolic Regression Technology.

• ISBN: 978-1-4614-1769-9
• Editorial: Springer New York
• Encuadernacion: Cartoné
• Páginas: 277
• Fecha Publicación: 28/12/2011
• Nº Volúmenes: 1
• Idioma: Inglés