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• EvoCOMNET Contributions.- Web Application Security through Gene Expression Programming.- Location Discovery in Wireless Sensor Networks Using a Two-Stage Simulated Annealing.- Wireless Communications for Distributed Navigation in Robot Swarms.- An Evolutionary Algorithm for Survivable Virtual Topology Mapping in Optical WDM Networks.- Extremal Optimization as a Viable Means for Mapping in Grids.- Swarm Intelligence Inspired Multicast Routing: An Ant Colony Optimization Approach.- A Framework for Evolutionary Peer-to-Peer Overlay Schemes.- Multiuser Scheduling in HSDPA with Particle Swarm Optimization.- Efficient Signal Processing and Anomaly Detection in Wireless Sensor Networks.- Peer-to-Peer Optimization in Large Unreliable Networks with Branch-and-Bound and Particle Swarms.- Evolving High-Speed, Easy-to-Understand Network Intrusion Detection Rules with Genetic Programming.- Soft Computing Techniques for Internet Backbone Traffic Anomaly Detection.- Testing Detector Parameterization Using Evolutionary Exploit Generation.- Ant Routing with Distributed Geographical Localization of Knowledge in Ad-Hoc Networks.- Discrete Particle Swarm Optimization for Multiple Destination Routing Problems.- EvoENVIRONMENT Contributions.- Combining Back-Propagation and Genetic Algorithms to Train Neural Networks for Ambient Temperature Modeling in Italy.- Estimating the Concentration of Nitrates in Water Samples Using PSO and VNS Approaches.- Optimal Irrigation Scheduling with Evolutionary Algorithms.- Adaptive Land-Use Management in Dynamic Ecological System.- EvoFIN Contributions.- Evolutionary Money Management.- Prediction of Interday Stock Prices Using Developmental and Linear Genetic Programming.- An Introduction to Natural Computing in Finance.- Evolutionary Approaches for Estimating a Coupled Markov Chain Model for Credit Portfolio Risk Management.- Knowledge Patterns in Evolutionary Decision Support Systems for Financial Time Series Analysis.- Predicting Turning Points in Financial Markets with Fuzzy-Evolutionary and Neuro-Evolutionary Modeling.- Comparison of Multi-agent Co-operative Co-evolutionary and Evolutionary Algorithms for Multi-objective Portfolio Optimization.- Dynamic High Frequency Trading: A Neuro-Evolutionary Approach.- EvoGAMES Contributions.- Decay of Invincible Clusters of Cooperators in the Evolutionary Prisoner's Dilemma Game.- Evolutionary Equilibria Detection in Non-cooperative Games.- Coevolution of Competing Agent Species in a Game-Like Environment.- Simulation Minus One Makes a Game.- Evolving Simple Art-Based Games.- Swarming for Games: Immersion in Complex Systems.- Fitness Diversity Parallel Evolution Algorithms in the Turtle Race Game.- Evolving Strategies for Non-player Characters in Unsteady Environments.- Grid Coevolution for Adaptive Simulations: Application to the Building of Opening Books in the Game of Go.- Evolving Teams of Cooperating Agents for Real-Time Strategy Game.- EvoHOT Contributions.- Design Optimization of Radio Frequency Discrete Tuning Varactors.- An Evolutionary Path Planner for Multiple Robot Arms.- Evolutionary Optimization of Number of Gates in PLA Circuits Implemented in VLSI Circuits.- Particle Swarm Optimisation as a Hardware-Oriented Meta-heuristic for Image Analysis.- EvoIASP Contributions.- A Novel GP Approach to Synthesize Vegetation Indices for Soil Erosion Assessment.- Flies Open a Door to SLAM.- Genetic Image Network for Image Classification.- Multiple Network CGP for the Classification of Mammograms.- Evolving Local Descriptor Operators through Genetic Programming.- Evolutionary Optimization for Plasmon-Assisted Lithography.- An Improved Multi-objective Technique for Fuzzy Clustering with Application to IRS Image Segmentation.- EvoINTERACTION Contributions.- Interactive Evolutionary Evaluation through Spatial Partitioning of Fitness Zones.- Fractal Evolver: Interactive Evolutionary Design of Fractals with Grid Computing.- Humorized Computational Intelligence towards User-Adapted Systems with a Sense of Humor.- Innovative Chance Discovery - Extracting Customers' Innovative Concept.- EvoMUSART Contributions.- Evolving Approximate Image Filters.- On the Role of Temporary Storage in Interactive Evolution.- Habitat: Engineering in a Simulated Audible Ecosystem.- The Evolution of Evolutionary Software: Intelligent Rhythm Generation in Kinetic Engine.- Filterscape: Energy Recycling in a Creative Ecosystem.- Evolved Ricochet Compositions.- Life's What You Make: Niche Construction and Evolutionary Art.- Global Expectation-Violation as Fitness Function in Evolutionary Composition.- Composing Using Heterogeneous Cellular Automata.- On the Socialization of Evolutionary Art.- An Evolutionary Music Composer Algorithm for Bass Harmonization.- Generation of Pop-Rock Chord Sequences Using Genetic Algorithms and Variable Neighborhood Search.- Elevated Pitch: Automated Grammatical Evolution of Short Compositions.- A GA-Based Control Strategy to Create Music with a Chaotic System.- Teaching Evolutionary Design Systems by Extending "Context Free".- Artificial Nature: Immersive World Making.- Evolving Indirectly Represented Melodies with Corpus-Based Fitness Evaluation.- Hearing Thinking.- EvoNUM Contributions.- Memetic Variation Local Search vs. Life-Time Learning in Electrical Impedance Tomography.- Estimating HMM Parameters Using Particle Swarm Optimisation.- Modeling Pheromone Dispensers Using Genetic Programming.- NK Landscapes Difficulty and Negative Slope Coefficient: How Sampling Influences the Results.- On the Parallel Speed-Up of Estimation of Multivariate Normal Algorithm and Evolution Strategies.- Adaptability of Algorithms for Real-Valued Optimization.- A Stigmergy-Based Algorithm for Continuous Optimization Tested on Real-Life-Like Environment.- Stochastic Local Search Techniques with Unimodal Continuous Distributions: A Survey.- Evolutionary Optimization Guided by Entropy-Based Discretization.- EvoSTOC Contributions.- The Influence of Population and Memory Sizes on the Evolutionary Algorithm's Performance for Dynamic Environments.- Differential Evolution with Noise Analyzer.- An Immune System Based Genetic Algorithm Using Permutation-Based Dualism for Dynamic Traveling Salesman Problems.- Dynamic Time-Linkage Problems Revisited.- The Dynamic Knapsack Problem Revisited: A New Benchmark Problem for Dynamic Combinatorial Optimisation.- Impact of Frequency and Severity on Non-Stationary Optimization Problems.- A Critical Look at Dynamic Multi-dimensional Knapsack Problem Generation.- EvoTRANSLOG Contributions.- Evolutionary Freight Transportation Planning.- An Effective Evolutionary Algorithm for the Cumulative Capacitated Vehicle Routing Problem.- A Corridor Method-Based Algorithm for the Pre-marshalling Problem.- Comparison of Metaheuristic Approaches for Multi-objective Simulation-Based Optimization in Supply Chain Inventory Management.- Heuristic Algorithm for Coordination in Public Transport under Disruptions.- Optimal Co-evolutionary Strategies for the Competitive Maritime Network Design Problem.
• (source: Nielsen Book Data)

The year 2009 celebrates the bicentenary of Darwin's birth and the 150th - niversary of the publication of his seminal work, On the Origin of Species.If this makes 2009 a special year for the research community working in biology and evolution, the ?eld of evolutionary computation (EC) also shares the same excitement. EC techniques are e?cient, nature-inspired planning and optimi- tion methods based on the principles of natural evolution and genetics. Due to their e?ciency and simple underlying principles, these methods can be used in the context of problem solving, optimization, and machine learning. A large and ever-increasing number of researchers and professionals make use of EC te- niques in various application domains. ThisvolumepresentsacarefulselectionofrelevantECapplicationscombi ned with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and can help and inspire researchers and professionals to develop e?cient EC methods for design and problem solving.
(source: Nielsen Book Data)

• EvoCOMNET contributions
• EvoFIN contributions
• EvoIASP contributions -- EvoINTERACTION contributions
• EvoMUSART contributions
• EvoSTOC contributions
• EvoTRANSLOG contributions.

This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2007, held in Valencia, Spain in April 2007. It examines evolutionary computation in communications, networks, and connected systems; finance and economics; image analysis and signal processing; and transportation and logistics. Coverage also details evolutionary algorithms in stochastic and dynamic environments.
(source: Nielsen Book Data)

• EvoCOMNET contributions
• EvoFIN contributions
• EvoIASP contributions -- EvoINTERACTION contributions
• EvoMUSART contributions
• EvoSTOC contributions
• EvoTRANSLOG contributions.

This book constitutes the refereed joint proceedings of seven workshops on evolutionary computing, EvoWorkshops 2007, held in Valencia, Spain in April 2007. It examines evolutionary computation in communications, networks, and connected systems; finance and economics; image analysis and signal processing; and transportation and logistics. Coverage also details evolutionary algorithms in stochastic and dynamic environments.
(source: Nielsen Book Data)

• Oral Contributions. Multiple Threshold Spatially Uniform ReliefF for the Genetic Analysis of Complex Human Diseases / Delaney Granizo-Mackenzie, Jason H. Moore
• Time-Point Specific Weighting Improves Coexpression Networks from Time-Course Experiments / Jie Tan, Gavin D. Grant, Michael L. Whitfield, Casey S. Greene
• Inferring Human Phenotype Networks from Genome-Wide Genetic Associations / Christian Darabos, Kinjal Desai, Richard Cowper-Sal·lari, Mario Giacobini
• Knowledge-Constrained K-Medoids Clustering of Regulatory Rare Alleles for Burden Tests / R. Michael Sivley, Alexandra E. Fish, William S. Bush
• Feature Selection and Classification of High Dimensional Mass Spectrometry Data: A Genetic Programming Approach / Soha Ahmed, Mengjie Zhang, Lifeng Peng
• Structured Populations and the Maintenance of Sex / Peter A. Whigham, Grant Dick, Alden Wright, Hamish G. Spencer
• Hybrid Multiobjective Artificial Bee Colony with Differential Evolution Applied to Motif Finding / David L. González-Álvarez, Miguel A. Vega-Rodríguez
• ACO-Based Bayesian Network Ensembles for the Hierarchical Classification of Ageing-Related Proteins / Khalid M. Salama, Alex A. Freitas
• Dimensionality Reduction via Isomap with Lock-Step and Elastic Measures for Time Series Gene Expression Classification / Carlotta Orsenigo, Carlo Vercellis
• Supervising Random Forest Using Attribute Interaction Networks / Qinxin Pan, Ting Hu, James D. Malley, Angeline S. Andrew, Margaret R. Karagas.

• Poster Contributions. Hybrid Genetic Algorithms for Stress Recognition in Reading / Nandita Sharma, Tom Gedeon
• Optimal Use of Biological Expert Knowledge from Literature Mining in Ant Colony Optimization for Analysis of Epistasis in Human Disease / Arvis Sulovari, Jeff Kiralis, Jason H. Moore
• A Multiobjective Proposal Based on the Firefly Algorithm for Inferring Phylogenies / Sergio Santander-Jiménez, Miguel A. Vega-Rodríguez
• Mining for Variability in the Coagulation Pathway: A Systems Biology Approach / Davide Castaldi, Daniele Maccagnola, Daniela Mari, Francesco Archetti
• Improving the Performance of CGPANN for Breast Cancer Diagnosis Using Crossover and Radial Basis Functions / Timmy Manning, Paul Walsh
• An Evolutionary Approach to Wetlands Design / Marco Gaudesi, Andrea Marion, Tommaso Musner, Giovanni Squillero, Alberto Tonda
• Impact of Different Recombination Methods in a Mutation-Specific MOEA for a Biochemical Application / Susanne Rosenthal, Nail El-Sourani, Markus Borschbach
• Cell-Based Metrics Improve the Detection of Gene-Gene Interactions Using Multifactor Dimensionality Reduction / Jonathan M. Fisher, Peter Andrews, Jeff Kiralis, Nicholas A. Sinnott-Armstrong
• Emergence of Motifs in Model Gene Regulatory Networks / Marcin Zagórski.

This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoMUSART and EvoApplications. The 10 revised full papers presented together with 9 poster papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics in the field of biological data analysis and computational biology. They address important problems in biology, from the molecular and genomic dimension to the individual and population level, often drawing inspiration from biological systems in oder to produce solutions to biological problems.
(source: Nielsen Book Data)

• Automatic Task Decomposition for the NeuroEvolution of Augmenting Topologies (NEAT) Algorithm / Timmy Manning and Paul Walsh
• Evolutionary Reaction Systems / Luca Manzoni, Mauro Castelli and Leonardo Vanneschi
• Optimizing the Edge Weights in Optimal Assignment Methods for Virtual Screening with Particle Swarm Optimization / Lars Rosenbaum, Andreas Jahn and Andreas Zell
• Lévy-Flight Genetic Programming: Towards a New Mutation Paradigm / Christian Darabos, Mario Giacobini, Ting Hu and Jason H. Moore
• Understanding Zooplankton Long Term Variability through Genetic Programming / Simone Marini and Alessandra Conversi
• Inferring Disease-Related Metabolite Dependencies with a Bayesian Optimization Algorithm / Holger Franken, Alexander Seitz, Rainer Lehmann, Hans-Ulrich Häring and Norbert Stefan, et al.
• A GPU-Based Multi-swarm PSO Method for Parameter Estimation in Stochastic Biological Systems Exploiting Discrete-Time Target Series / Marco S. Nobile, Daniela Besozzi, Paolo Cazzaniga, Giancarlo Mauri and Dario Pescini
• Tracking the Evolution of Cooperation in Complex Networked Populations / Flávio L. Pinheiro, Francisco C. Santos and Jorge M. Pacheco
• GeNet: A Graph-Based Genetic Programming Framework for the Reverse Engineering of Gene Regulatory Networks / Leonardo Vanneschi, Matteo Mondini, Martino Bertoni, Alberto Ronchi and Mattia Stefano
• Comparing Multiobjective Artificial Bee Colony Adaptations for Discovering DNA Motifs / David L. González-Álvarez, Miguel A. Vega-Rodríguez, Juan A. Gómez-Pulido and Juan M. Sánchez-Pérez
• The Role of Mutations in Whole Genome Duplication / Qinxin Pan, Christian Darabos and Jason H. Moore
• Comparison of Methods for Meta-dimensional Data Analysis Using in Silico and Biological Data Sets / Emily R. Holzinger, Scott M. Dudek, Alex T. Frase, Brooke Fridley and Prabhakar Chalise, et al.

• Inferring Phylogenetic Trees Using a Multiobjective Artificial Bee Colony Algorithm / Sergio Santander-Jiménez, Miguel A. Vega-Rodríguez, Juan A. Gómez-Pulido and Juan M. Sánchez-Pérez
• Prediction of Mitochondrial Matrix Protein Structures Based on Feature Selection and Fragment Assembly / Gualberto Asencio-Cortés, Jesús S. Aguilar-Ruiz, Alfonso E. Márquez-Chamorro, Roberto Ruiz and Cosme E. Santiesteban-Toca
• Feature Selection for Lung Cancer Detection Using SVM Based Recursive Feature Elimination Method / Kesav Kancherla and Srinivas Mukkamala
• Measuring Gene Expression Noise in Early Drosophila Embryos: The Highly Dynamic Compartmentalized Micro-environment of the Blastoderm Is One of the Main Sources of Noise / Alexander V. Spirov, Nina E. Golyandina, David M. Holloway, Theodore Alexandrov and Ekaterina N. Spirova, et al.
• Artificial Immune Systems Perform Valuable Work When Detecting Epistasis in Human Genetic Datasets / Delaney Granizo-Mackenzie and Jason H. Moore
• A Biologically Informed Method for Detecting Associations with Rare Variants / Carrie C. Buchanan, John R. Wallace, Alex T. Frase, Eric S. Torstenson and Sarah A. Pendergrass, et al.
• Complex Detection in Protein-Protein Interaction Networks: A Compact Overview for Researchers and Practitioners / Clara Pizzuti, Simona E. Rombo and Elena Marchiori
• Short-Range Interactions and Decision Tree-Based Protein Contact Map Predictor / Cosme E. Santiesteban-Toca, Gualberto Asencio-Cortés, Alfonso E. Márquez-Chamorro and Jesús S. Aguilar-Ruiz
• A NSGA-II Algorithm for the Residue-Residue Contact Prediction / Alfonso E. Márquez-Chamorro, Federico Divina, Jesús S. Aguilar-Ruiz, Jaume Bacardit and Gualberto Asencio-Cortés, et al.
• In Silico Infection of the Human Genome / W.B. Langdon and M.J. Arno
• Improving Phylogenetic Tree Interpretability by Means of Evolutionary Algorithms / Francesco Cerutti, Luigi Bertolotti, Tony L. Goldberg and Mario Giacobini.

This book constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, held in Málaga, Spain, in April 2012 co-located with the Evo* 2012 events. The 15 revised full papers presented together with 8 poster papers were carefully reviewed and selected from numerous submissions. Computational Biology is a wide and varied discipline, incorporating aspects of statistical analysis, data structure and algorithm design, machine learning, and mathematical modeling toward the processing and improved understanding of biological data. Experimentalists now routinely generate new information on such a massive scale that the techniques of computer science are needed to establish any meaningful result. As a consequence, biologists now face the challenges of algorithmic complexity and tractability, and combinatorial explosion when conducting even basic analyses.

This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2011, held in Torino, Italy, in April 2011 co-located with the Evo 2011 events. The 12 revised full papers presented together with 7 poster papers were carefully reviewed and selected from numerous submissions. All papers included topics of interest such as biomarker discovery, cell simulation and modeling, ecological modeling, fluxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, and systems biology.
(source: Nielsen Book Data)

• Variable Genetic Operator Search for the Molecular Docking Problem.- Variable Genetic Operator Search for the Molecular Docking Problem.- Role of Centrality in Network-Based Prioritization of Disease Genes.- Parallel Multi-Objective Approaches for Inferring Phylogenies.- An Evolutionary Model Based on Hill-Climbing Search Operators for Protein Structure Prediction.- Finding Gapped Motifs by a Novel Evolutionary Algorithm.- Top-Down Induction of Phylogenetic Trees.- A Model Free Method to Generate Human Genetics Datasets with Complex Gene-Disease Relationships.- Grammatical Evolution of Neural Networks for Discovering Epistasis among Quantitative Trait Loci.- Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions.- Identification of Individualized Feature Combinations for Survival Prediction in Breast Cancer: A Comparison of Machine Learning Techniques.- Correlation-Based Scatter Search for Discovering Biclusters from Gene Expression Data.- A Local Search Appproach for Transmembrane Segment and Signal Peptide Discrimination.- A Replica Exchange Monte Carlo Algorithm for the Optimization of Secondary Structure Packing in Proteins.- Improving Multi-Relief for Detecting Specificity Residues from Multiple Sequence Alignments.- Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models.- Posters.- The Informative Extremes: Using Both Nearest and Farthest Individuals Can Improve Relief Algorithms in the Domain of Human Genetics.- Artificial Immune Systems for Epistasis Analysis in Human Genetics.- Metaheuristics for Strain Optimization Using Transcriptional Information Enriched Metabolic Models.- Using Rotation Forest for Protein Fold Prediction Problem: An Empirical Study.- Towards Automatic Detecting of Overlapping Genes - Clustered BLAST Analysis of Viral Genomes.- Investigating Populational Evolutionary Algorithms to Add Vertical Meaning in Phylogenetic Trees.
• (source: Nielsen Book Data)

The ?eld of bioinformatics has two main objectives: the creation and main- nance of biological databases, and the discovery of knowledge from life sciences datainordertounravelthemysteriesofbiologicalfunction, leadingtonewdrugs andtherapiesforhumandisease. Life sciencesdatacomeinthe formofbiological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model speci?c information in a given dataset in order to generate new interesting knowledge. Computer science methods such as evolutionary computation, machine learning, and data mining all have a great deal to o?er the ?eld of bioinformatics. The goal of the 8th - ropean Conference on Evolutionary Computation, Machine Learning, and Data Mining in Bioinformatics (EvoBIO 2010) was to bring together experts in these ?elds in order to discuss new and novel methods for tackling complex biological problems. The 8th EvoBIO conference was held in Istanbul, Turkey during April 7-9, 2010attheIstanbulTechnicalUniversity. EvoBIO2010washeldjointlywiththe 13th European Conference on Genetic Programming (EuroGP 2010), the 10th European Conference on Evolutionary Computation in Combinatorial Opti- sation (EvoCOP 2010), and the conference on the applications of evolutionary computation, EvoApplications. Collectively, the conferences areorganizedunder the name Evo* (www. evostar. org). EvoBIO, held annually as a workshop since 2003, became a conference in 2007 and it is now the premiere European event for those interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology.
(source: Nielsen Book Data)

• Association Study between Gene Expression and Multiple Relevant Phenotypes with Cluster Analysis.- Gaussian Graphical Models to Infer Putative Genes Involved in Nitrogen Catabolite Repression in S. cerevisiae.- Chronic Rat Toxicity Prediction of Chemical Compounds Using Kernel Machines.- Simulating Evolution of Drosophila Melanogaster Ebony Mutants Using a Genetic Algorithm.- Microarray Biclustering: A Novel Memetic Approach Based on the PISA Platform.- F-score with Pareto Front Analysis for Multiclass Gene Selection.- A Hierarchical Classification Ant Colony Algorithm for Predicting Gene Ontology Terms.- Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks.- Optimal Use of Expert Knowledge in Ant Colony Optimization for the Analysis of Epistasis in Human Disease.- On the Efficiency of Local Search Methods for the Molecular Docking Problem.- A Comparison of Genetic Algorithms and Particle Swarm Optimization for Parameter Estimation in Stochastic Biochemical Systems.- Guidelines to Select Machine Learning Scheme for Classification of Biomedical Datasets.- Evolutionary Approaches for Strain Optimization Using Dynamic Models under a Metabolic Engineering Perspective.- Clustering Metagenome Short Reads Using Weighted Proteins.- A Memetic Algorithm for Phylogenetic Reconstruction with Maximum Parsimony.- Validation of a Morphogenesis Model of Drosophila Early Development by a Multi-objective Evolutionary Optimization Algorithm.- Refining Genetic Algorithm Based Fuzzy Clustering through Supervised Learning for Unsupervised Cancer Classification.
• (source: Nielsen Book Data)

The ?eld of bioinformatics has two main objectives: the creation and main- nance of biological databases, and the discovery of knowledge from life sciences datainordertounravelthemysteriesofbiologicalfunction, leadingtonewdrugs andtherapiesforhumandisease.Life sciencesdatacomeinthe formofbiological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model speci?c information in a given dataset in order to generate new interesting knowledge. Computer science methods such as evolutionary computation, machine learning, and data mining all have a great deal to o?er the ?eld of bioinformatics. The goal of the 7th - ropean Conference on Evolutionary Computation, Machine Learning, and Data Mining in Bioinformatics (EvoBIO 2009) was to bring together experts in these ?elds in order to discuss new and novel methods for tackling complex biological problems. The 7th EvoBIO conference was held in Tubing .. en, Germany during April 15-17, 2009 at the Eberhard-Karls-Universitat .. Tu ..bingen. EvoBIO 2009 was held jointly with the 12th European Conference on Genetic Programming (- roGP 2009), the 9th European Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP 2009), and the Evo Workshops. C- lectively, the conferences and workshops are organized under the name Evo* (www.evostar.org).
(source: Nielsen Book Data)

• 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. .