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Genetic and Evolutionary Computing: Proceedings of the Fifteenth International Conference on Genetic and Evolutionary Computing (Volume I), October 6–8, 2023, Kaohsiung, Taiwan (Lecture Notes in Electrical Engineering #1145)
by Jerry Chun-Wei Lin Chin-Shiuh Shieh Mong-Fong Horng Shu-Chuan ChuThis first book of conference proceedings contains selected papers presented at ICGEC 2023, the 15th International Conference on Genetic and Evolutionary Computing, held on October 6–8, 2023, in Kaohsiung, Taiwan. The conference is intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing. And the readers know the up-to-date techniques of the mentioned topics, including swarm intelligence and its applications, operational technologies and networked multimedia applications, wearable computing and intelligent data hiding, image processing and intelligent applications, and intelligent multimedia tools and applications. It helps readers bring new ideas or apply the designed approaches from the collected papers to their professional jobs.
Genetic and Evolutionary Computing: Proceedings of the Thirteenth International Conference on Genetic and Evolutionary Computing, November 1–3, 2019, Qingdao, China (Advances in Intelligent Systems and Computing #1107)
by Jeng-Shyang Pan Shu-Chuan Chu Jerry Chun-Wei Lin Yongquan LiangThis book gathers papers presented at the 13th International Conference on Genetic and Evolutionary Computing (ICGEC 2019), which was held in Qingdao, China, from 1st to 3rd, November 2019. Since it was established, in 2006, the ICGEC conference series has been devoted to new approaches with a focus on evolutionary computing. Today, it is a forum for the researchers and professionals in all areas of computational intelligence including evolutionary computing, machine learning, soft computing, data mining, multimedia and signal processing, swarm intelligence and security. The book appeals to policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, and other professionals in the learning industry, and further and continuing education.
Genetic and Evolutionary Computing: Proceedings of the Twelfth International Conference on Genetic and Evolutionary Computing, December 14-17, Changzhou, Jiangsu, China (Advances in Intelligent Systems and Computing #834)
by Jeng-Shyang Pan Jerry Chun-Wei Lin Bixia Sui Shih-Pang TsengThis volume of Advances in Intelligent Systems and Computing highlights papers presented at the 12th International Conference on Genetic and Evolutionary Computing (ICGEC 2018). Held from 14 to 17 December 2018 in Changzhou, Jiangsu, China, the conference was co-sponsored by Springer, Changzhou College of Information Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of Technology, National Demonstration Center for Experimental Electronic Information and Electrical Technology Education, Fujian University of Technology, Tajen University, National University of Kaohsiung, and Shandong University of Science and Technology, China. The conference is intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing.
Genetic and Evolutionary Computing
by Jeng-Shyang Pan Jerry Chun-Wei Lin Chia-Hung Wang Xin Hua JiangThis book gathers papers presented at the 10th International Conference on Genetic and Evolutionary Computing (ICGEC 2016). The conference was co-sponsored by Springer, Fujian University of Technology in China, the University of Computer Studies in Yangon, University of Miyazaki in Japan, National Kaohsiung University of Applied Sciences in Taiwan, Taiwan Association for Web Intelligence Consortium, and VSB-Technical University of Ostrava, Czech Republic. The ICGEC 2016, which was held from November 7 to 9, 2016 in Fuzhou City, China, was intended as an international forum for researchers and professionals in all areas of genetic and evolutionary computing.
Genetic and Evolutionary Computing: Proceedings of the Fifteenth International Conference on Genetic and Evolutionary Computing (Volume II), October 6-8, 2023, Kaohsiung, Taiwan (Lecture Notes in Electrical Engineering #1114)
by Jeng-Shyang Pan Zhigeng Pan Pei Hu Jerry Chun-Wei LinThis second volume of conference proceedings contains selected papers presented at ICGEC 2023, the 15th International Conference on Genetic and Evolutionary Computing, held on October 6-8, 2023 in Kaohsiung, Taiwan. The conference is intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing. And the readers may know the up-to-date techniques of the mentioned topics, including technologies for next-generation network environments, recent progress in computational electromagnetic dynamics, future cyber security, privacy and forensics for advanced systems, data mining techniques and its applications, optimization models in deep learning and machine learning. It will help readers bring new ideas or apply the designed approaches from the collected papers to their professional jobs.
Genetic Programming: 21st European Conference, EuroGP 2018, Parma, Italy, April 4-6, 2018, Proceedings (Lecture Notes in Computer Science #10781)
by Mauro Castelli Lukas Sekanina Mengjie Zhang Stefano Cagnoni Pablo García-SánchezThis book constitutes the refereed proceedings of the 21st European Conference on Genetic Programming, EuroGP 2018, held in Parma, Italy, in April 2018, co-located with the Evo* 2018 events, EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics and applications including analysis of feature importance for metabolomics, semantic methods, evolution of boolean networks, generation of redundant features, ensembles of GP models, automatic design of grammatical representations, GP and neuroevolution, visual reinforcement learning, evolution of deep neural networks, evolution of graphs, and scheduling in heterogeneous networks.
Genetic Programming: 27th European Conference, EuroGP 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings (Lecture Notes in Computer Science #14631)
by Mario Giacobini Bing Xue Luca ManzoniThis book constitutes the refereed proceedings of the 27th European Conference on Genetic Programming, EuroGP 2024, held in Aberystwyth, UK, April 3–5, 2024 and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EvoApplications.The 13 papers (9 selected for long presentation and 4 for short presentation) collected in this book were carefully reviewed and selected from 24 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, as well as exploring GP applications to the optimization of machine learning methods and the evolution of control policies.
Genetic Programming
by Malcolm I. Heywood James Mcdermott Mauro Castelli Ernesto Costa Kevin SimThis book constitutes the refereed proceedings of the19th European Conference on Genetic Programming, EuroGP 2016, held in Porto,Portugal, in March/April 2016 co-located with the Evo*2016 events: EvoCOP,EvoMUSART, and EvoApplications. The 11 revised full papers presented togetherwith 8 poster papers were carefully reviewed and selected from 36 submissions. The wide range of topics in this volume reflects the current state of researchin the field. Thus, we see topics as diverse as semantic methods, recursiveprograms, grammatical methods, coevolution, Cartesian GP, feature selection,metaheuristics, evolvability, and fitness predictors; and applicationsincluding image processing, one-class classification, SQL injection attacks,numerical modelling, streaming data classification, creation and optimisationof circuits, multi-class classification, scheduling in manufacturing andwireless networks.
Genetic Programming: 24th European Conference, EuroGP 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings (Lecture Notes in Computer Science #12691)
by Ting Hu Nuno Lourenço Eric MedvetThis book constitutes the refereed proceedings of the 24th European Conference on Genetic Programming, EuroGP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events, EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers and 6 short papers presented in this book were carefully reviewed and selected from 27 submissions. The wide range of topics in this volume reflects the current state of research in the field. The collection of papers cover interesting topics including developing new operators for variants of GP algorithms, as well as exploring GP applications to the optimisation of machine learning methods and the evolution of complex combinational logic circuits.
Genetic Programming: 23rd European Conference, EuroGP 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings (Lecture Notes in Computer Science #12101)
by Nuno Lourenço Ting Hu Eric Medvet Federico DivinaThis book constitutes the refereed proceedings of the 23rd European Conference on Genetic Programming, EuroGP 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EvoCOP, EvoMUSART and EvoApplications.The 12 full papers and 6 short papers presented in this book were carefully reviewed and selected from 36 submissions. The papers cover a wide spectrum of topics, including designing GP algorithms for ensemble learning, comparing GP with popular machine learning algorithms, customising GP algorithms for more explainable AI applications to real-world problems.
Genetic Programming
by James Mcdermott Mauro Castelli Lukas Sekanina Evert Haasdijk Pablo García-SánchezThis book constitutes the refereed proceedings of the 18th European Conference on Genetic Programming, EuroGP 2015, held in Copenhagen, Spain, in April 2015 co-located with the Evo 2015 events, EvoCOP, Evo MUSART and Evo Applications. The 12 revised full papers presented together with 6 poster papers were carefully reviewed and selected form 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics as diverse as semantic methods, recursive programs, grammatical methods, coevolution, Cartesian GP, feature selection, initialisation procedures, ensemble methods and search objectives; and applications including text processing, cryptography, numerical modelling, software parallelisation, creation and optimisation of circuits, multi-class classification, scheduling and artificial intelligence.
Genetic Programming: 25th European Conference, EuroGP 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20–22, 2022, Proceedings (Lecture Notes in Computer Science #13223)
by Eric Medvet Gisele Pappa Bing XueThis book constitutes the refereed proceedings of the 25th European Conference on Genetic Programming, EuroGP 2022, held as part of Evo*2021, as Virtual Event, in April 2022, co-located with the Evo*2022 events, EvoCOP, EvoMUSART, and EvoApplications. The 12 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 35 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 operators for variants of GP algorithms, as well as exploring GP applications to the optimization of machine learning methods and the evolution of complex combinational logic circuits.
Genetic Programming: 26th European Conference, EuroGP 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (Lecture Notes in Computer Science #13986)
by Gisele Pappa Mario Giacobini Zdenek VasicekThis 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.
Genetic Programming: 22nd European Conference, EuroGP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings (Lecture Notes in Computer Science #11451)
by Lukas Sekanina Ting Hu Nuno Lourenço Hendrik Richter Pablo García-SánchezThis 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.
Genetic Programming for Image Classification: An Automated Approach to Feature Learning (Adaptation, Learning, and Optimization #24)
by Mengjie Zhang Ying Bi Bing XueThis book offers several new GP approaches to feature learning for image classification. Image classification is an important task in computer vision and machine learning with a wide range of applications. Feature learning is a fundamental step in image classification, but it is difficult due to the high variations of images. Genetic Programming (GP) is an evolutionary computation technique that can automatically evolve computer programs to solve any given problem. This is an important research field of GP and image classification. No book has been published in this field. This book shows how different techniques, e.g., image operators, ensembles, and surrogate, are proposed and employed to improve the accuracy and/or computational efficiency of GP for image classification. The proposed methods are applied to many different image classification tasks, and the effectiveness and interpretability of the learned models will be demonstrated. This book is suitable as a graduate and postgraduate level textbook in artificial intelligence, machine learning, computer vision, and evolutionary computation.
Genetic Programming for Production Scheduling: An Evolutionary Learning Approach (Machine Learning: Foundations, Methodologies, and Applications)
by Fangfang Zhang Su Nguyen Yi Mei Mengjie ZhangThis book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP’s performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future.Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.
Genetic Programming Theory and Practice X
by Ekaterina Vladislavleva Marylyn D Ritchie Jason H. Moore Rick RioloThese contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of injecting expert knowledge in evolutionary search, analysis of problem difficulty and required GP algorithm complexity, foundations in running GP on the cloud - communication, cooperation, flexible implementation, and ensemble methods. Additional focal points for GP symbolic regression are: (1) The need to guarantee convergence to solutions in the function discovery mode; (2) Issues on model validation; (3) The need for model analysis workflows for insight generation based on generated GP solutions - model exploration, visualization, variable selection, dimensionality analysis; (4) Issues in combining different types of data. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Programming Theory and Practice XII
by Rick Riolo William P. Worzel Mark KotanchekThese contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer function, and highly distributed genetic programming systems. Application areas include chemical process control, circuit design, financial data mining and bioinformatics. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Programming Theory and Practice XIII
by Rick Riolo W. P. Worzel Mark Kotanchek Arthur KordonThese contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Programming Theory and Practice XIV (Genetic and Evolutionary Computation)
by Rick Riolo Bill Worzel Brian Goldman Bill TozierThese contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Chapters in this volume include: Similarity-based Analysis of Population Dynamics in GP Performing Symbolic RegressionHybrid Structural and Behavioral Diversity Methods in GPMulti-Population Competitive Coevolution for Anticipation of Tax EvasionEvolving Artificial General Intelligence for Video Game ControllersA Detailed Analysis of a PushGP RunLinear Genomes for Structured ProgramsNeutrality, Robustness, and Evolvability in GPLocal Search in GPPRETSL: Distributed Probabilistic Rule Evolution for Time-Series ClassificationRelational Structure in Program Synthesis Problems with Analogical ReasoningAn Evolutionary Algorithm for Big Data Multi-Class Classification ProblemsA Generic Framework for Building Dispersion Operators in the Semantic SpaceAssisting Asset Model Development with Evolutionary AugmentationBuilding Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Programming Theory and Practice XIX (Genetic and Evolutionary Computation)
by Leonardo Trujillo Stephan M. Winkler Sara Silva Wolfgang BanzhafThis 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.
Genetic Programming Theory and Practice XV (Genetic and Evolutionary Computation)
by Wolfgang Banzhaf Randal S. Olson William Tozier Rick RioloThese contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: exploiting subprograms in genetic programming, schema frequencies in GP, Accessible AI, GP for Big Data, lexicase selection, symbolic regression techniques, co-evolution of GP and LCS, and applying ecological principles to GP. It also covers several chapters on best practices and lessons learned from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Programming Theory and Practice XVII (Genetic and Evolutionary Computation)
by Wolfgang Banzhaf Erik Goodman Leigh Sheneman Leonardo Trujillo Bill WorzelThese contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. In this year’s edition, the topics covered include many of the most important issues and research questions in the field, such as: opportune application domains for GP-based methods, game playing and co-evolutionary search, symbolic regression and efficient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms.The volume includes several chapters on best practices and lessons learned from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Programming Theory and Practice XVIII (Genetic and Evolutionary Computation)
by Leonardo Trujillo Wolfgang Banzhaf Bill Worzel Stephan WinklerThis book, written by the foremost international researchers and practitioners of genetic programming (GP), explores the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. In this year’s edition, the topics covered include many of the most important issues and research questions in the field, such as opportune application domains for GP-based methods, game playing and co-evolutionary search, symbolic regression and efficient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms. The book includes several chapters on best practices and lessons learned from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Programming Theory and Practice XX (Genetic and Evolutionary Computation)
by Stephan Winkler Leonardo Trujillo Charles Ofria Ting HuGenetic 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 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.