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Название: Genetic Programming Theory and Practice XIX
Автор: Leonardo Trujillo · Stephan M. Winkler, Sara Silva, Wolfgang Banzhaf
Издательство: Springer
Год: 2023
Страниц: 272
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
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. We present a GUI-driven and efficient Genetic Programming (GP) and AI Planning framework designed for agent-based learning research. Our framework, ABL-Unity3D, is built in Unity3D, a game development environment.
Автор: Leonardo Trujillo · Stephan M. Winkler, Sara Silva, Wolfgang Banzhaf
Издательство: Springer
Год: 2023
Страниц: 272
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
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. We present a GUI-driven and efficient Genetic Programming (GP) and AI Planning framework designed for agent-based learning research. Our framework, ABL-Unity3D, is built in Unity3D, a game development environment.