Evolutionary Computation in Dynamic and Uncertain Environments

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Publisher : Springer Science & Business Media
ISBN 13 : 3540497722
Total Pages : 614 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Evolutionary Computation in Dynamic and Uncertain Environments by : Shengxiang Yang

Download or read book Evolutionary Computation in Dynamic and Uncertain Environments written by Shengxiang Yang and published by Springer Science & Business Media. This book was released on 2007-03-07 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.

Evolutionary Multi-objective Optimization in Uncertain Environments

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Publisher : Springer Science & Business Media
ISBN 13 : 3540959750
Total Pages : 273 pages
Book Rating : 4.5/5 (49 download)

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Book Synopsis Evolutionary Multi-objective Optimization in Uncertain Environments by : Chi-Keong Goh

Download or read book Evolutionary Multi-objective Optimization in Uncertain Environments written by Chi-Keong Goh and published by Springer Science & Business Media. This book was released on 2009-03-09 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined. The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of evolutionary multi-objective optimization and uncertainties.

Evolutionary Optimization in Dynamic Environments

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Publisher : Springer Science & Business Media
ISBN 13 : 1461509114
Total Pages : 217 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Evolutionary Optimization in Dynamic Environments by : Jürgen Branke

Download or read book Evolutionary Optimization in Dynamic Environments written by Jürgen Branke and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. Evolutionary Optimization in Dynamic Environments is the first comprehensive work on the application of EAs to dynamic optimization problems. It provides an extensive survey on research in the area and shows how EAs can be successfully used to continuously and efficiently adapt a solution to a changing environment, find a good trade-off between solution quality and adaptation cost, find robust solutions whose quality is insensitive to changes in the environment, find flexible solutions which are not only good but that can be easily adapted when necessary. All four aspects are treated in this book, providing a holistic view on the challenges and opportunities when applying EAs to dynamic optimization problems. The comprehensive and up-to-date coverage of the subject, together with details of latest original research, makes Evolutionary Optimization in Dynamic Environments an invaluable resource for researchers and professionals who are dealing with dynamic and stochastic optimization problems, and who are interested in applying local search heuristics, such as evolutionary algorithms.

Evolutionary Computation for Dynamic Optimization Problems

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Publisher : Springer
ISBN 13 : 3642384161
Total Pages : 470 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Evolutionary Computation for Dynamic Optimization Problems by : Shengxiang Yang

Download or read book Evolutionary Computation for Dynamic Optimization Problems written by Shengxiang Yang and published by Springer. This book was released on 2013-11-18 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.

Parallel Problem Solving from Nature -- PPSN XIII

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Publisher : Springer
ISBN 13 : 3319107623
Total Pages : 955 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Parallel Problem Solving from Nature -- PPSN XIII by : Thomas Bartz-Beielstein

Download or read book Parallel Problem Solving from Nature -- PPSN XIII written by Thomas Bartz-Beielstein and published by Springer. This book was released on 2014-09-11 with total page 955 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Parallel Problem Solving from Nature, PPSN 2013, held in Ljubljana, Slovenia, in September 2014. The total of 90 revised full papers were carefully reviewed and selected from 217 submissions. The meeting began with 7 workshops which offered an ideal opportunity to explore specific topics in evolutionary computation, bio-inspired computing and metaheuristics. PPSN XIII also included 9 tutorials. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; classifier system, differential evolution and swarm intelligence; coevolution and artificial immune systems; constraint handling; dynamic and uncertain environments; estimation of distribution algorithms and metamodelling; genetic programming; multi-objective optimisation; parallel algorithms and hardware implementations; real world applications; and theory.

Evolutionary Computation in Scheduling

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Publisher : John Wiley & Sons
ISBN 13 : 1119573874
Total Pages : 323 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Evolutionary Computation in Scheduling by : Amir H. Gandomi

Download or read book Evolutionary Computation in Scheduling written by Amir H. Gandomi and published by John Wiley & Sons. This book was released on 2020-04-09 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering.

Applications of Evolutionary Computation

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Publisher : Springer
ISBN 13 : 3642205259
Total Pages : 367 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Applications of Evolutionary Computation by : Cecilia Di Chio

Download or read book Applications of Evolutionary Computation written by Cecilia Di Chio and published by Springer. This book was released on 2011-04-27 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2011, held in Torino, Italy, in April 2011 colocated with the Evo* 2011 events. Thanks to the large number of submissions received, the proceedings for EvoApplications 2011 are divided across two volumes (LNCS 6624 and 6625). The present volume contains contributions for EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC. The 36 revised full papers presented were carefully reviewed and selected from numerous submissions. This volume presents an overview about the latest research in EC. Areas where evolutionary computation techniques have been applied range from telecommunication networks to complex systems, finance and economics, games, image analysis, evolutionary music and art, parameter optimization, scheduling, and logistics. These papers may provide guidelines to help new researchers tackling their own problem using EC.

Designing Evolutionary Algorithms for Dynamic Environments

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Publisher : Springer Science & Business Media
ISBN 13 : 3662065606
Total Pages : 155 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Designing Evolutionary Algorithms for Dynamic Environments by : Ronald W. Morrison

Download or read book Designing Evolutionary Algorithms for Dynamic Environments written by Ronald W. Morrison and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Details robustness, stability, and performance of Evolutionary Algorithms in dynamic environments

Applications of Evolutionary Computing

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Publisher : Springer
ISBN 13 : 3642371922
Total Pages : 639 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Applications of Evolutionary Computing by : Anna I. Esparcia-Alcázar

Download or read book Applications of Evolutionary Computing written by Anna I. Esparcia-Alcázar and published by Springer. This book was released on 2013-03-12 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART. The 65 revised full papers presented were carefully reviewed and selected from 119 submissions. EvoApplications 2013 consisted of the following 12 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary computation in robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

Parallel Problem Solving from Nature - PPSN X

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Publisher : Springer
ISBN 13 : 3540877002
Total Pages : 1183 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Parallel Problem Solving from Nature - PPSN X by : Günter Rudolph

Download or read book Parallel Problem Solving from Nature - PPSN X written by Günter Rudolph and published by Springer. This book was released on 2008-09-16 with total page 1183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.

Variants of Evolutionary Algorithms for Real-World Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3642234240
Total Pages : 466 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Variants of Evolutionary Algorithms for Real-World Applications by : Raymond Chiong

Download or read book Variants of Evolutionary Algorithms for Real-World Applications written by Raymond Chiong and published by Springer Science & Business Media. This book was released on 2011-11-13 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book “Variants of Evolutionary Algorithms for Real-World Applications” aims to promote the practitioner’s view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others. These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation.

Applications of Evolutionary Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 3540787607
Total Pages : 724 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Applications of Evolutionary Computing by : Mario Giacobini

Download or read book Applications of Evolutionary Computing written by Mario Giacobini and published by Springer Science & Business Media. This book was released on 2008-03-14 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of eight European workshops on the Theory and Applications of Evolutionary Computation, EvoWorkshops 2008, held in Naples, Italy, in March 2008 within the scope of the EvoStar 2008 event. The 57 revised full papers and 18 revised short papers presented were carefully reviewed and selected from a total of 133 submissions. In accordance with the eight workshops covered, the papers are organized in topical sections on application of nature-inspired techniques to telecommunication networks and other connected systems, evolutionary computation in finance and economics, bio-inspired heuristics for design automation, evolutionary computation in image analysis and signal processing, evolutionary and biologically inspired music, sound, art and design, bio-inspired algorithms for continuous parameter optimization, evolutionary algorithms in stochastic and dynamic environments, theory and applications of evolutionary computation, and on evolutionary computation in transportation and logistics.

Advances in Learning Automata and Intelligent Optimization

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Publisher : Springer Nature
ISBN 13 : 3030762912
Total Pages : 340 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Advances in Learning Automata and Intelligent Optimization by : Javidan Kazemi Kordestani

Download or read book Advances in Learning Automata and Intelligent Optimization written by Javidan Kazemi Kordestani and published by Springer Nature. This book was released on 2021-06-23 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits • Presents the latest advances in learning automata-based optimization approaches. • Addresses the memetic models of learning automata for solving NP-hard problems. • Discusses the application of learning automata for behavior control in evolutionary computation in detail. • Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

Swarm, Evolutionary, and Memetic Computing

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Publisher : Springer
ISBN 13 : 3319037536
Total Pages : 776 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Swarm, Evolutionary, and Memetic Computing by : Bijaya Ketan Panigrahi

Download or read book Swarm, Evolutionary, and Memetic Computing written by Bijaya Ketan Panigrahi and published by Springer. This book was released on 2013-12-13 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 8297 and LNCS 8298 constitutes the proceedings of the 4th International Conference on Swarm, Evolutionary and Memetic Computing, SEMCCO 2013, held in Chennai, India, in December 2013. The total of 123 papers presented in this volume set was carefully reviewed and selected for inclusion in the proceedings. They cover cutting-edge research on swarm, evolutionary and memetic computing, neural and fuzzy computing and its application.

Applications of Evolutionary Computation

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Publisher : Springer
ISBN 13 : 3319775383
Total Pages : 917 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Applications of Evolutionary Computation by : Kevin Sim

Download or read book Applications of Evolutionary Computation written by Kevin Sim and published by Springer. This book was released on 2018-03-07 with total page 917 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the 21st International Conference on the Applications of Evolutionary Computation, EvoApplications 2018, held in Parma, Italy, in April 2018, collocated with the Evo* 2018 events EuroGP, EvoCOP, and EvoMUSART. The 59 revised full papers presented were carefully reviewed and selected from 84 submissions. EvoApplications 2018 combined research from 14 different domains: business analytics and finance (EvoBAFIN); computational biology (EvoBIO); communication networks and other parallel and distributed systems (EvoCOMNET); complex systems (EvoCOMPLEX); energy-related optimization (EvoENERGY); games and multi-agent systems (EvoGAMES); image analysis, signal processing and pattern recognition (EvoIASP); realworld industrial and commercial environments (EvoINDUSTRY); knowledge incorporation in evolutionary computation (EvoKNOW); continuous parameter optimization (EvoNUM); parallel architectures and distributed infrastructures (EvoPAR); evolutionary robotics (EvoROBOT); nature-inspired algorithms in software engineering and testing (EvoSET); and stochastic and dynamic environments (EvoSTOC).

Recent Advances in Evolutionary Multi-objective Optimization

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Publisher : Springer
ISBN 13 : 3319429787
Total Pages : 179 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Recent Advances in Evolutionary Multi-objective Optimization by : Slim Bechikh

Download or read book Recent Advances in Evolutionary Multi-objective Optimization written by Slim Bechikh and published by Springer. This book was released on 2016-08-09 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.

Advances in Computation and Intelligence

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Publisher : Springer
ISBN 13 : 3642048439
Total Pages : 554 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Advances in Computation and Intelligence by : Zhenhua Li

Download or read book Advances in Computation and Intelligence written by Zhenhua Li and published by Springer. This book was released on 2009-09-30 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volumes CCIS 51 and LNCS 5812 constitute the proceedings of the Fourth Interational Symposium on Intelligence Computation and Applications, ISICA 2009, held in Huangshi, China, during October 23-25. ISICA 2009 attracted over 300 submissions. Through rigorous reviews, 58 papers were included in LNCS 5821, and 54 papers were collected in CCIS 51. ISICA conferences are one of the first series of international conferences on computational intelligence that combine elements of learning, adaptation, evolution and fuzzy logic to create programs as alternative solutions to artificial intelligence.