4 New Genetic Programming Books Defining 2025

The methods Mario Giacobini, Bing Xue, and Luca Manzoni developed while organizing and editing the proceedings of the EuroGP 2024 conference reveal the cutting-edge landscape of genetic programming research. This collection provides you with detailed insights into new algorithm variants and practical applications, such as optimizing machine learning techniques and evolving control policies. By presenting peer-reviewed papers from experts actively advancing the field, it equips you with the latest strategies and experimental results shaping genetic programming today. If you're engaged in AI research or developing advanced evolutionary algorithms, this volume offers a focused look at emerging trends and technical depth that fuels innovation.

Stephan Winkler and his co-authors bring together leading researchers who explore fresh perspectives in Genetic Programming, blending theory and application in ways that reflect the field's dynamic evolution. You’ll find detailed discussions on symbolic regression, innovative selection mechanisms, and modular strategies that push the boundaries of evolutionary machine learning. This book also examines how Genetic Programming intersects with pressing challenges like cybersecurity and biomedicine, offering you insight into both the methodology and its real-world impact. If you’re interested in the latest research trends and practical implementations, this volume serves as a focused window into current developments.

This personalized book explores the cutting-edge algorithmic strategies transforming genetic programming in 2025. Tailored to your background and interests, it reveals the newest developments and breakthroughs reshaping the field today. Through focused chapters, it examines emerging techniques, advances in evolutionary models, and key discoveries defining this revolutionary era. By matching your specific goals, the book offers a deep dive into how 2025 innovations are pushing the boundaries of genetic programming practice and research. Readers gain a clear understanding of the latest trends and future directions, enabling a highly relevant and engaging learning experience tailored to the rapidly evolving landscape.

After exploring recent advances in computational biology, authors Mohana Naga Vamsi and Allam Apparao present a focused study on gene regulatory networks through a novel genetic programming technique. This book dives into the mechanics of fitting ordinary differential equation models to time series gene expression data, demonstrating how their algorithm surpasses established methods like BANJO and GRNGen in precision and sensitivity. You'll gain insights into decoding complex gene regulation, including applications to the GABA signalling network in the rat brain, making it especially useful if you're working on bioinformatics or systems biology. It's a technical read best suited for those familiar with genetic algorithms and computational intelligence in biological contexts.

After analyzing recent advances in evolutionary computation, the authors assembled this volume to showcase novel research that pushes the boundaries of Genetic Programming. You’ll explore a variety of innovative techniques, from GP-based symbolic regression models to unique selection mechanisms that refine evolutionary search processes. The book also dives into modular GP strategies and practical applications in fields like cybersecurity and biomedicine, offering insights grounded in both theory and practice. If you’re invested in understanding where Genetic Programming stands today and how it’s being applied in real-world scenarios, this collection will sharpen your grasp of emerging trends and methodologies.