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• Intro
• Preface
• Organization
• Contents
• Long Presentations
• A Self-Adaptive Approach to Exploit Topological Properties of Different GAs' Crossover Operators
• 1 Introduction
• 2 Fundamental Concepts
• 2.1 Crossover
• 2.2 Convex Combination, Convex Hull, and Convex Search
• 3 Related Works
• 4 Methodology
• 4.1 Dynamic Diversity Maintenance
• 4.2 Self-adaptive Crossover
• 5 Experimental Settings
• 6 Experimental Results
• 7 Conclusions
• References
• A Genetic Programming Encoder for Increasing Autoencoder Interpretability
• 1 Introduction
• 1.1 Structure

• 2 Background and Related Work
• 2.1 Non-linear Dimensionality Reduction
• 2.2 Evolutionary Computation for Dimensionality Reduction
• 2.3 Genetic Programming for Autoencoding
• 3 Proposed Method: GPE-AE
• 3.1 GP Representation of Encoder
• 3.2 Fitness Evaluation
• 3.3 Decoder Architecture
• 4 Experiment Design
• 4.1 Comparison Methods
• 4.2 Evaluation Measures
• 4.3 Datasets
• 5 Results
• 6 Further Analysis
• 7 Conclusions
• References
• Graph Networks as Inductive Bias for Genetic Programming: Symbolic Models for Particle-Laden Flows
• 1 Introduction

• 2 Background and Related Work
• 2.1 Genetic Programming in Physics Applications
• 2.2 Machine Learning for Particle-Laden Flows
• 3 Proposed Methods
• 3.1 Graph Networks
• 3.2 Genetic Programming
• 4 Experiment Design
• 4.1 Data Generation: Simulation of Particle-Laden Flows
• 4.2 Data Preprocessing
• 4.3 Algorithm Settings
• 5 Results and Analysis
• 5.1 Overall Algorithm Performance
• 5.2 Explainability of Equations
• 5.3 Validation of Symbolic Models
• 6 Conclusion and Future Work
• References
• Phenotype Search Trajectory Networks for Linear Genetic Programming

• 1 Introduction
• 2 The LGP System
• 2.1 Boolean LGP Algorithm
• 2.2 Genotype, Phenotype, and Fitness
• 3 Kolmogorov Complexity
• 4 Sampling and Metrics Estimation
• 5 Search Trajectory Networks
• 5.1 General Definitions
• 5.2 The Proposed STN Models
• 5.3 Network Visualisation
• 5.4 Comparing Three Targets with Increasing Difficulty
• 6 Discussion
• References
• GPAM: Genetic Programming with Associative Memory
• 1 Introduction
• 2 Related Work
• 2.1 Symbolic Regression and Genetic Programming
• 2.2 Efficient Processing of DNNs
• 2.3 Weight Compression
• 3 Proposed Method

• 3.1 The GPAM Approach
• 3.2 GPAM for Weight Generation
• 4 Results for Symbolic Regression Benchmarks
• 4.1 Benchmarks
• 4.2 Setup
• 4.3 Memory Sizing
• 4.4 Role of Constants in GPAM
• 5 Results for Weight Generation
• 6 Discussion and Conclusions
• References
• MAP-Elites with Cosine-Similarity for Evolutionary Ensemble Learning
• 1 Introduction
• 2 Related Work
• 2.1 Semantic GP
• 2.2 GP-Based Ensemble Learning
• 2.3 Quality Diversity Optimization
• 3 The Proposed Ensemble Learning Algorithm
• 3.1 The Overall Framework
• 3.2 Angle-Based Dimensionality Reduction

This book constitutes the refereed proceedings of the 26th European Conference on Genetic Programming, EuroGP 2023, held as part of EvoStar 2023, in Brno, Czech Republic, during April 12-14, 2023, and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EvoApplications. The 14 revised full papers and 8 short papers presented in this book were carefully reviewed and selected from 38 submissions. The wide range of topics in this volume reflects the current state of research in the field. The collection of papers cover topics including developing new variants of GP algorithms for both optimization and machine learning problems as well as exploring GP to address complex real-world problems. .

• Contributing Authors.- Preface.- Foreword.- Genetic Programming: Theory and Practice.- Better Solutions Faster: Soft Evolution of Robust Regression Models in Pareto Genetic Programming.- Manipulation of Convergence in Evolutionary Systems.- Large-Scale, Time-Constrained Symbolic Regression-Classification.- Solving Complex Problems in Human Genetics Using Genetic Programming.- Towards an Information Theoretic Framework for Genetic Programming.- Investigating Problem Hardness in Real Life Applications.- Improving the Scalability of Generative Representations for Open-Ended Design.- Program Structure-Fitness Disconnect and Its Impact on Evolution in GP.- Genetic Programming with Reuse of Known Designs.- Robust Engineering Design of Electronic Circuits with Active Components Using Genetic Programming and Bond Graphs.- Trustable Symbolic Regression Models.- Improving Performance and Cooperation in Multi-Agent Systems.- An Empirical Study of Multi-Objective Algorithms for Stock Ranking.- Using GP and Cultural Algorithms to Simulate the Evolution of an Ancient Urban Center.- Index.
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Genetic Programming Theory and Practice V was developed from the fifth workshop at the University of Michigan's Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application. The work covers applications of GP to a wide variety of domains, including bioinformatics, symbolic regression for system modeling, financial modeling, circuit design and robot controllers. This volume is a unique and indispensable tool for academics, researchers and industry professionals involved in GP, evolutionary computation, machine learning and artificial intelligence.
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• Plenary Talks.- A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms.- An Empirical Boosting Scheme for ROC-Based Genetic Programming Classifiers.- Confidence Intervals for Computational Effort Comparisons.- Crossover Bias in Genetic Programming.- Density Estimation with Genetic Programming for Inverse Problem Solving.- Empirical Analysis of GP Tree-Fragments.- Empirical Comparison of Evolutionary Representations of the Inverse Problem for Iterated Function Systems.- Evolution of an Efficient Search Algorithm for the Mate-In-N Problem in Chess.- Fast Genetic Programming on GPUs.- FIFTHTM: A Stack Based GP Language for Vector Processing.- Genetic Programming with Fitness Based on Model Checking.- Geometric Particle Swarm Optimisation.- GP Classifier Problem Decomposition Using First-Price and Second-Price Auctions.- Layered Learning in Boolean GP Problems.- Mining Distributed Evolving Data Streams Using Fractal GP Ensembles.- Multi-objective Genetic Programming for Improving the Performance of TCP.- On Population Size and Neutrality: Facilitating the Evolution of Evolvability.- On the Limiting Distribution of Program Sizes in Tree-Based Genetic Programming.- Predicting Prime Numbers Using Cartesian Genetic Programming.- Real-Time, Non-intrusive Evaluation of VoIP.- Training Binary GP Classifiers Efficiently: A Pareto-coevolutionary Approach.- Posters.- A Comprehensive View of Fitness Landscapes with Neutrality and Fitness Clouds.- Analysing the Regularity of Genomes Using Compression and Expression Simplification.- Changing the Genospace: Solving GA Problems with Cartesian Genetic Programming.- Code Regulation in Open Ended Evolution.- Data Mining of Genetic Programming Run Logs.- Evolving a Statistics Class Using Object Oriented Evolutionary Programming.- Evolving Modular Recursive Sorting Algorithms.- Fitness Landscape Analysis and Image Filter Evolution Using Functional-Level CGP.- Genetic Programming Heuristics for Multiple Machine Scheduling.- Group-Foraging with Particle Swarms and Genetic Programming.- Multiple Interactive Outputs in a Single Tree: An Empirical Investigation.- Parsimony Doesn't Mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data.- The Holland Broadcast Language and the Modeling of Biochemical Networks.- The Induction of Finite Transducers Using Genetic Programming.
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This book constitutes the refereed proceedings of the 10th European Conference on Genetic Programming, EuroGP 2007, held in Valencia, Spain in April 2007 colocated with EvoCOP 2007. The 21 revised plenary papers and 14 revised poster papers were carefully reviewed and selected from 71 submissions. The papers address fundamental and theoretical issues, along with a wide variety of papers dealing with different application areas.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 9th European Conference on Genetic Programming, EuroGP 2006, held in Budapest, Hungary, in April 2006, colocated with EvoCOP 2006. The 21 revised plenary papers and 11 revised poster papers were carefully reviewed and selected from 59 submissions. The papers address fundamental and theoretical issues, along with a wide variety of papers dealing with different application areas, such as computer science, engineering, machine learning, Kolmogorov complexity, biology and computational design, showing that GP is a powerful and practical problem-solving paradigm.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 7th European Conference on Genetic Programming, EuroGP 2004, held in Coimbra, Portugal, in April 2004. The 38 revised papers presented were carefully reviewed and selected from 61 submissions. The papers deal with a variety of foundational and methodological issues as well as with advanced applications in areas like engineering, computer science, language understanding, bioinformatics, and design.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 6th European Conference on Genetic Programming, EuroGP 2003, held in Essex, UK in April 2003. The 45 revised papers presented were carefully reviewed and selected from 61 submissions. All current aspects of genetic programming and genetic algorithms are addressed, ranging from foundational, theoretical, and methodological issues to advanced applications in various fields.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 4th European Conference on Genetic Programming, EuroGP 2001, held at Lake Como, Italy in April 2001. The 17 revised full papers and 13 research posters presented were carefully reviewed and selected during a rigorous double-blind refereeing process out of 42 submissions. All current aspects of genetic programming are addressed, ranging from theoretical and foundational issues to applications in a variety of fields such as robotics, artificial retina, character recognition, financial prediction, digital filter and electronic circuit design, image processing, data fusion, and bio-sequencing.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the Third European Conference on Genetic Programming, EuroGP 2000, held in Scotland, UK, in April 2000. The 14 revised full papers presented together with 13 short papers were carefully reviewed and selected from a total of 39 submissions. All relevant aspects of genetic programming are addressed, ranging from theoretical and foundational issues to applications in a variety of fields such as automatic design, pattern recognition, robotic control, music and image processing, and symbolic regression.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the Second European Workshop on Genetic Programming, EuroPG '99, held in Goteborg, Sweden in May 1999.The 12 revised full papers and 11 posters presented have been carefully reviewed and selected for inclusion in the book. All the relevant aspects of genetic programming are addressed ranging from traditional and foundational issues to applications in a variety of fields.
(source: Nielsen Book Data)

• The volume presents 12 revised full papers and 10 short presentations carefully selected for inclusion in the book. The papers are organized in topical sections on experimental and theoretical studies
• algorithms, representations and operators
• and applications.
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This book constitutes the refereed proceedings of the First European Workshop on Genetic Programming, EuroGP'98, held in Paris, France, in April 1998, under the sponsorship of EvoNet, the European Network of Excellence in Evolutionary Computing. The volume presents 12 revised full papers and 10 short presentations carefully selected for inclusion in the book. The papers are organized in topical sections on experimental and theoretical studies; algorithms, representations and operators; and applications.
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 8th European Conference on Genetic Programming, EuroGP 2005, held in Lausanne, Switzerland in March/April 2005.The 20 revised plenary papers and 14 revised poster papers were carefully reviewed and selected from 64 submissions. Some of the papers deal with foundational, theoretical, or methodological aspects of genetic programming; others focus on applications in various areas, such as computer science, engineering, language processing, biology, and computational design, demonstrating that genetic programming is a powerful and practical problem solving tool.
(source: Nielsen Book Data)

• Genetic Programming Theory and Practice.- Discovering Financial Technical Trading Rules Using.- Abstraction GP.- Using Genetic Programming in Industrial Statistical Model Building Population Sizing for Genetic Programming.- Considering the Roles of Structure in Problem Solving by Computer.- Lessons Learned using Genetic Programming in a Stock Picking Context Favourable Biasing of Function Sets.- Toward Automated Design of Industrial-Strength Analog Circuits by Means of Genetic Programming.- Topological Synthesis of Robust Systems.- Does Genetic Programming Inherently Adopt Structured DesignTechniques?- Genetic Programming of an Algorithmic Chemistry.- ACGP: Adaptable Constrained Genetic Programming.- Searching for Supply Chain Reordering Policies.- Cartesian Genetic Programming and the Post Docking Filtering Problem.- Listening to Data: Tuning a Genetic Programming System.- Incident Detection on Highways.- Pareto-Front Exploitation in Symbolic Regression.- An Evolved Antenna for a NASA Mission.
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The work described in this book was first presented at the Second Workshop on Genetic Programming, Theory and Practice, organized by the Center for the Study of Complex Systems at the University of Michigan, Ann Arbor, 13-15 May 2004. The goal of this workshop series is to promote the exchange of research results and ideas between those who focus on Genetic Programming (GP) theory and those who focus on the application of GP to various re- world problems. In order to facilitate these interactions, the number of talks and participants was small and the time for discussion was large. Further, participants were asked to review each other's chapters before the workshop. Those reviewer comments, as well as discussion at the workshop, are reflected in the chapters presented in this book. Additional information about the workshop, addendums to chapters, and a site for continuing discussions by participants and by others can be found at http://cscs.umich.edu:8000/GPTP-20041. We thank all the workshop participants for making the workshop an exciting and productive three days. In particular we thank all the authors, without whose hard work and creative talents, neither the workshop nor the book would be possible. We also thank our keynote speakers Lawrence ("Dave") Davis of NuTech Solutions, Inc., Jordan Pollack of Brandeis University, and Richard Lenski of Michigan State University, who delivered three thought-provoking speeches that inspired a great deal of discussion among the participants.
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• [I]. Long presentations: 1. Ariadne : evolving test data using grammatical evolution / Muhammad Sheraz Anjum, Conor Ryan
• 2. Quantum program synthesis : swarm algorithms and benchmarks / Timothy Atkinson, Athena Karsa, John Drake, Jerry Swan
• 3. A genetic programming approach to predict mosquitoes abundance / Riccardo Gervasi, Irene Azzali, Donal Bisanzio, Andrea Mosca, Luigi Bertolotti, Mario Giacobini
• 4. Complex network analysis of a genetic programming phenotype network / Ting Hu, Marco Tomassini, Wolfgang Banzhof
• 5. Improving genetic programming with novel exploration : exploitation control / Jonathan Kelly, Erik Hemberg, Una-May O'Reilly
• 6. Towards a scalable EA-based optimization of digital circuits / Jitka Kocnova, Zdenek Vasicek
• 7. Cartesian genetic programming as an optimizer of programs evolved with geometric semantic genetic programming / Ondrej Koncal, Lukas Sekanina
• 8. Can genetic programming do manifold learning too? / Andrew Lensen, Bing Xue, Mengjie Zhang
• 9. Why is auto-encoding difficult for genetic programming? / James McDermott
• 10. Solution and fitness evolution (SAFE) : coevolving solutions and their objective functions / Moshe Sipper, James H. Moore, Ryan J. Urbanowicz
• 11. A model of external memory for navigation in partially observable visual reinforcement learning tasks / Robert J. Smith, Malcolm I. Heywood
• 12. Fault detection and classification for induction motors using genetic programming / Yu Zhang, Ting Hu, Xiaodong Liang, Mohammad Zawad Ali, Md. Nasmus Sakib Khan Shabbir.

• [II]. Short presentations: 13. Fast DENSER : efficient deep NeuroEvolution / Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
• 14. A vectorial approach to genetic programming / Irene Azzali, Leonardo Vanneschi, Sara Silva, Illya Bakurov, Mario Giacobini
• 15. Comparison of genetic programming methods on design of cryptographic Boolean functions / Jakub Husa
• 16. Evolving AVX512 parallel C code using GP / William B. Langdon, Ronny Lorenz
• 17. Hyper-bent Boolean functions and evolutionary algorithms / Luca Mariot, Domagoj Jakobovic, Alberto Leporati, Stjepan Picek
• 18. Learning class disjointness axioms using grammatical evolution / Thu Huong Nguyen, Andrea G.B. Tettamanzi.

This book constitutes the refereed proceedings of the 22nd European Conference on Genetic Programming, EuroGP 2019, held as part of Evo* 2019, in Leipzig, Germany, in April 2019, co-located with the Evo* events EvoCOP, EvoMUSART, and EvoApplications. The 12 revised full papers and 6 short papers presented in this volume were carefully reviewed and selected from 36 submissions. They cover a wide range of topics and reflect the current state of research in the field. With a special focus on real-world applications in 2019, the papers are devoted to topics such as the test data design in software engineering, fault detection and classification of induction motors, digital circuit design, mosquito abundance prediction, machine learning and cryptographic function design. .
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011, held in Torino, Italy, in April 2011 co-located with the Evo* 2011 events. This 20 revised full papers presented together with 9 poster papers were carefully reviewed and selected from 59 submissions. The wide range of topics in this volume reflect the current state of research in the field, including representations, theory, novel operators and techniques, self organization, and applications.
(source: Nielsen Book Data)