Genetic Programming Theory and Practice XXI
Alexander Lalejini (Hrsg.), Ting Hu (Hrsg.), Stephan M. Winkler (Hrsg.), Wolfgang Banzhaf (Hrsg.)
Naturwissenschaften, Medizin, Informatik, Technik / Informatik
Beschreibung
This book brings together some of the most impactful researchers in the field of genetic programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year´s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine, and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state-of-the-art in GP research.
Kundenbewertungen
Ethics in Computer Science, Program Synthesis, Model Discovery, Automatic Modelling, Evolutionary Machine Learning, Genetic Programming, Symbolic Regression, Evolutionary Art, Genetic Improvement, Genetic Programming Applications, Bioinformatics, Genetic Programming Theory, Artificial Evolution, LLMs, Lexicase Selection