{"product_id":"genetic-programming-theory-and-practice-xiv-von-rick-riolo-bill-worzel-brian-goldman-bill-tozier-bill-tozier-hrsg","title":"Genetic Programming Theory and Practice XIV","description":"\n                                \n                \u003cp\u003e\u003c\/p\u003e\n                                \n                \u003cp\u003eThese 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. Chapters in this volume include: \u003c\/p\u003e\n                                \n                \n                \u003cp\u003e\u003c\/p\u003e\n                                \n                \u003cul\u003e\n                                        \n                    \u003cli\u003e\n                                                Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Hybrid Structural and Behavioral Diversity Methods in GP\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Multi-Population Competitive Coevolution for Anticipation of Tax Evasion\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Evolving Artificial General Intelligence for Video Game Controllers\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                A Detailed Analysis of a PushGP Run\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Linear Genomes for Structured Programs\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Neutrality, Robustness, and Evolvability in GP\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Local Search in GP\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Relational Structure in Program Synthesis Problems with Analogical Reasoning\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                An Evolutionary Algorithm for Big Data Multi-Class Classification Problems\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                A Generic Framework for Building Dispersion Operators in the Semantic Space\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003e\n                                                Assisting Asset Model Development with Evolutionary Augmentation\n                        \n                        \u003cbr\u003e\n                                            \n                    \u003c\/li\u003e\n                                        \n                    \u003cli\u003eBuilding Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool \u003c\/li\u003e\n                                    \n                \u003c\/ul\u003e\n                                 \n                \n                \u003cp\u003eReaders 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.\u003c\/p\u003e\n                                \n                \u003cbr\u003e\n                                \n                \u003cp\u003e\u003c\/p\u003e\n                            \n            \u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783319970875\"\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783030073008\"\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e","brand":"Libri","offers":[{"title":"Hardcover - 9783319970875","offer_id":32990848024669,"sku":"9783319970875","price":53.49,"currency_code":"EUR","in_stock":true},{"title":"Softcover - 9783030073008","offer_id":39419340816477,"sku":"9783030073008","price":53.49,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/a59e1dbf-2434-47bf-9605-d339e9e62100.jpg?v=1772342926","url":"https:\/\/shop.autorenwelt.de\/products\/genetic-programming-theory-and-practice-xiv-von-rick-riolo-bill-worzel-brian-goldman-bill-tozier-bill-tozier-hrsg","provider":"Autorenwelt Shop","version":"1.0","type":"link"}