Genetic programming theory and practice XXII Bogdan Burlacu, Fabricio Olivetti de França, Alexander Lalejini, Stephen Kelly, Wolfgang Banzhaf, editors

Format:

Book

Author/Creator:

Burlacu, Bogdan.

Contributor:

Burlacu, Bogdan, editor.

Olivetti de França, Fabricio, editor.

Lalejini, Alexander, editor.

Kelly, Stephen, editor.

Banzhaf, Wolfgang, 1955- editor.

Series:

Genetic and evolutionary computation series 1932-0175

Genetic and Evolutionary Computation 1932-0175

Language:

English

Subjects (All):

Genetic programming (Computer science).

Physical Description:

1 online resource

Other Title:

Genetic programming theory and practice 22

Place of Publication:

Singapore Springer 2026

Summary:

Genetic Programming Theory and Practice 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 volume 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

Contents:

Chapter 1. On the Effects of Continuous Pruning on Symbolic Regression for Different Variants of Evolutionary Search

Chapter 2. Analyzing Fitness Aggregation Strategies for Symbolic Regression Problem-Solving

Chapter 3. The Evolution of Heterogeneous Logic: An Analysis of the Buffet Method

Chapter 4. FPGA-Based Streaming Processors for Tree-Based Genetic Programming

Chapter 5. On Interpretability in Multimodal Biomedical Image Analysis

Chapter 6. CANTS-GP: A Nature-Inspired Metaheuristic for Graph Based Genetic Programs

Chapter 7. Bridging Genetic Programming and Type Theory Research

Chapter 8. To Smoothly Go Where No Model has Gone Before: Pareto Tournaments, Model Curvature and Alternating Objectives

Chapter 9. GP and LLMs for Program Synthesis: No ClearWinners

Chapter 10. Offline reinforcement learning: A New Challenge for Symbolic Regression

Chapter 11. Language Model-Driven Program Synthesis with Program Trace Optimization on the Abstraction and Reasoning Corpus

Chapter 12. Evolving Programs in the Lambda Calculus using Program Trace Optimisation

Chapter 13. Interpretable Control with Graph-based Genetic Programming

Chapter 14. Decoupling Representation and Learning in Genetic Programming:the LaSER Approach

Chapter 15. Tips on Effective Theory and Practice of Genetic Programming

Chapter 16. Spatial Genetic Programming with the S1 Processing Board

Chapter 17. Applications of Evolutionary Algorithms for Instrument Design

Chapter 18. Agentic GP: A Theoretical Framework for the Development of Genetic Programming Systems via Agentic AI

Chapter 19. Evolution of Artificial Intelligence, Continued

Chapter 20. Heeding Good Advice: Scaling Down and Specializing in the Age of Big AI

Chapter 21. The Gegelati Framework for Efficient and Reproducible Solutions with Tangled Program Graphs

Notes:

Online resource; title from PDF title page (SpringerLink, viewed July 17, 2026)

ISBN:

9789819563982

9819563984

OCLC:

1605532696

Access Restriction:

Restricted for use by site license