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Evolutionary Multi-Objective System Design: Theory and Applications (Chapman & Hall/CRC Computer and Information Science Series)
by Nadia Nedjah Luiza De Macedo Mourelle Heitor Silverio LopesReal-world engineering problems often require concurrent optimization of several design objectives, which are conflicting in cases. This type of optimization is generally called multi-objective or multi-criterion optimization. The area of research that applies evolutionary methodologies to multi-objective optimization is of special and growing interest. It brings a viable computational solution to many real-world problems. Generally, multi-objective engineering problems do not have a straightforward optimal design. These kinds of problems usually inspire several solutions of equal efficiency, which achieve different trade-offs. Decision makers’ preferences are normally used to select the most adequate design. Such preferences may be dictated before or after the optimization takes place. They may also be introduced interactively at different levels of the optimization process. Multi-objective optimization methods can be subdivided into classical and evolutionary. The classical methods usually aim at a single solution while the evolutionary methods provide a whole set of so-called Pareto-optimal solutions. Evolutionary Multi-Objective System Design: Theory and Applications provides a representation of the state-of-the-art in evolutionary multi-objective optimization research area and related new trends. It reports many innovative designs yielded by the application of such optimization methods. It also presents the application of multi-objective optimization to the following problems: Embrittlement of stainless steel coated electrodes Learning fuzzy rules from imbalanced datasets Combining multi-objective evolutionary algorithms with collective intelligence Fuzzy gain scheduling control Smart placement of roadside units in vehicular networks Combining multi-objective evolutionary algorithms with quasi-simplex local search Design of robust substitution boxes Protein structure prediction problem Core assignment for efficient network-on-chip-based system design
Evolutionary Multi-Task Optimization: Foundations and Methodologies (Machine Learning: Foundations, Methodologies, and Applications)
by Liang Feng Abhishek Gupta Kay Chen Tan Yew Soon OngA remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be used to enhance problem-solving in other related tasks. In machine learning, the idea of leveraging relevant information across related tasks as inductive biases to enhance learning performance has attracted significant interest. In contrast, attempts to emulate the human brain’s ability to generalize in optimization – particularly in population-based evolutionary algorithms – have received little attention to date. Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems, each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks. This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.
Evolutionary Multiobjective Optimization: Theoretical Advances and Applications (Advanced Information and Knowledge Processing)
by Ajith Abraham Robert GoldbergEvolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.
Evolutionary Optimization (International Series in Operations Research & Management Science #48)
by Masoud Mohammadian Ruhul Sarker Xin Xin YaoEvolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.
Evolutionary Optimization in Dynamic Environments (Genetic Algorithms and Evolutionary Computation #3)
by Jürgen BrankeEvolutionary 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 Optimization: the µGP toolkit
by Ernesto Sanchez Massimiliano Schillaci Giovanni SquilleroThis book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled μGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers.For a practitioner, μGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.For an evolutionary computation researcher, μGP may be regarded as a platform where new operators and strategies can be easily tested.MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/
Evolutionary Psychology and Digital Games: Digital Hunter-Gatherers (Routledge Advances in Game Studies)
by Johannes Breuer Daniel Pietschmann Benny Liebold Benjamin P. LangeEvolutionary Psychology and Digital Games: Digital Hunter-Gatherers is the first edited volume that systematically applies evolutionary psychology to the study of the use and effects of digital games. The book is divided into four parts: Theories and Methods Emotion and Morality Social Interaction Learning and Motivation These topics reflect the main areas of digital games research as well as some of the basic categories of psychological research. The book is meant as a resource for researchers and graduate students in psychology, anthropology, media studies and communication as well as video game designers who are interested in learning more about the evolutionary roots of player behaviors and experiences.
Evolutionary Psychology and Digital Games: Digital Hunter-Gatherers (Routledge Advances in Game Studies)
by Johannes Breuer Daniel Pietschmann Benny Liebold Benjamin P. LangeEvolutionary Psychology and Digital Games: Digital Hunter-Gatherers is the first edited volume that systematically applies evolutionary psychology to the study of the use and effects of digital games. The book is divided into four parts: Theories and Methods Emotion and Morality Social Interaction Learning and Motivation These topics reflect the main areas of digital games research as well as some of the basic categories of psychological research. The book is meant as a resource for researchers and graduate students in psychology, anthropology, media studies and communication as well as video game designers who are interested in learning more about the evolutionary roots of player behaviors and experiences.
Evolutionary Psychology and Information Systems Research: A New Approach to Studying the Effects of Modern Technologies on Human Behavior (Integrated Series in Information Systems #24)
by Ned KockThis book is a compilation of chapters written by leading researchers from all over the world. Those researchers’ common characteristic is that they have investigated issues at the intersection of the elds of information systems (IS) and evoluti- ary psychology (EP). The main goal of this book is to serve as a reference for IS research building on EP concepts and theories (in short, IS-EP research). The book is organized in three main parts: Part I focuses on EP concepts and theories that can be used as a basis for IS-EP research; Part II provides several exemplars of IS-EP research in practice; and Part III summarizes emerging issues and debate that can inform IS-EP research, including debate regarding philosophical foundations and credibility of related ndings. IS-EP research is generally concerned with the use of concepts and theories from EP in the study of IS, particularly regarding the impact of modern information and communication technologies on the behavior of individuals, groups, and organi- tions. From a practitioners’ perspective, the most immediate consumers of IS-EP research are those who develop and use IS, of which a large contingent are in bu- nesses that employ IS to support marketing, order-taking, production, and delivery of goods and services. In this context, IS-EP ndings may be particularly useful due to the present need to design web-based interfaces that will be used by in- viduals from different cultures, and often different countries, and whose common denominator is their human nature.
Evolutionary Robotics. From Intelligent Robotics to Artificial Life: International Symposium, ER 2001, Tokyo, Japan, October 18-19, 2001. Proceedings (Lecture Notes in Computer Science #2217)
by Takashi GomiThis book constitutes the refereed proceedings of the 8th International Symposium on Evolutionary Robotics, ER 2001, held in Tokyo, Japan, in October 2001.The seven revised full papers by the invited speakers Rodney A. Brooks, Dario Floreano, Robert J. Full, Inman Harvey, Owen Holland, Francesco Mondada, and Jordan B. Pollack were carefully selected and revised for presentation in the book. Among the topics addressed are imitation of life and machine consciousness, autonomous vision-based robots, evolved robots, living machines, artificial evolution, bioinspired artificial life locomotion, and mobile robotic systems engineering.
Evolutionary Scheduling (Studies in Computational Intelligence #49)
by Keshav Dahal Kay Chen Tan Peter I. CowlingEvolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.
Evolutionary Search and the Job Shop: Investigations on Genetic Algorithms for Production Scheduling (Production and Logistics)
by Dirk C. MattfeldProduction scheduling dictates highly constrained mathematical models with complex and often contradicting objectives. Evolutionary algorithms can be formulated almost independently of the detailed shaping of the problems under consideration. As one would expect, a weak formulation of the problem in the algorithm comes along with a quite inefficient search. This book discusses the suitability of genetic algorithms for production scheduling and presents an approach which produces results comparable with those of more tailored optimization techniques.
Evolutionary Statistical Procedures: An Evolutionary Computation Approach to Statistical Procedures Designs and Applications (Statistics and Computing)
by Roberto Baragona Francesco Battaglia Irene PoliThis proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions are infeasible. Evolutionary algorithms represent a powerful and easily understood means of approximating the optimum value in a variety of settings. The proposed text seeks to guide readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods (including both stand-alone evolutionary algorithms and hybrid crosses of these procedures with standard statistical algorithms like Metropolis-Hastings) in a variety of applications. This book would serve as an excellent reference work for statistical researchers at an advanced graduate level or beyond, particularly those with a strong background in computer science.
Evolutionary Swarm Robotics: Evolving Self-Organising Behaviours in Groups of Autonomous Robots (Studies in Computational Intelligence #108)
by Vito TrianniIn this book the use of ER techniques for the design of self-organising group behaviours, for both simulated and real robots is introduced. The book tries to mediate between two apparently opposed perspectives: engineering and cognitive science. The experiments presented in the book and the results obtained contribute to the assessment of ER not only as a design tool, but also as a methodology for modelling and understanding intelligent adaptive behaviours.
Evolutionary Synthesis of Pattern Recognition Systems (Monographs in Computer Science)
by Bir Bhanu Yingqiang Lin Krzysztof KrawiecIntegrates computer vision, pattern recognition, and AI. Presents original research that will benefit researchers and professionals in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology
Evolutionary Trends of the Internet: 2001 Thyrrhenian International Workshop on Digital Communications, IWDC 2001, Taormina, Italy, September 17-20, 2001. Proceedings (Lecture Notes in Computer Science #2170)
by Sergio PalazzoThis book constitutes the refereed proceedings of the Thyrrhenian International Workshop on Digital Communication, IWDC 2001, held in Taormina, Italy in September 2001.The 46 revised full papers presented are a mix of invited papers and selected submitted papers and reflect the state of the art in multiservice IP network research and development. The book offers topical sections on WDM technologies for the next generation Internet, mobile and wireless Internet access, QoS in the next generation Internet, multicast and routing in IP networks, mulitmedia services over the Internet, performance of Internet protocols, dynamic service management, and source encoding and Internet applications.
Evolutionary Web Development (Applied Computing)
by Arno ScharlExamining the evolution of Web information systems, this text pays particular attention to the emergent attributes of electronic markets. Arno Scharl identifies four categories of architecture and demonstrates their virtues and limitations: static, interactive, adaptive, and agent- mediated systems. He presents an automated and scalable approach to Web assessment, emphasizing the role of feedback in an iterative cycle of design, implementation, usage, and analysis. Evolutionary Web Development blends a strong theoretical background with state-of-the-art research and several industry analyses, making it a valuable resource for researchers and students, as well as for practitioners looking for effective methods and tools. Further information available at http://webdev.wu-wien.ac.at/
Evolutionary Wind Turbine Placement Optimization with Geographical Constraints
by Daniel LückeheDaniel Lückehe presents different approaches to optimize locations of multiple wind turbines on a topographical map. The author succeeds in significantly improving placement solutions by employing optimization heuristics. He proposes various real-world scenarios that represent real planning situations. Advanced evolutionary heuristics for the turbine placement optimization create not only highly optimized solutions but also significantly different solutions to give decision-makers optimal choices. As a matter of fact, wind turbines play an important role towards green energy supply. An optimal location is essential to achieve the highest possible energy efficiency.
Evolvable Components: From Theory to Hardware Implementations (Natural Computing Series)
by Lukas SekaninaAt the beginning of the 1990s research started in how to combine soft comput ing with reconfigurable hardware in a quite unique way. One of the methods that was developed has been called evolvable hardware. Thanks to evolution ary algorithms researchers have started to evolve electronic circuits routinely. A number of interesting circuits - with features unreachable by means of con ventional techniques - have been developed. Evolvable hardware is quite pop ular right now; more than fifty research groups are spread out over the world. Evolvable hardware has become a part of the curriculum at some universi ties. Evolvable hardware is being commercialized and there are specialized conferences devoted to evolvable hardware. On the other hand, surprisingly, we can feel the lack of a theoretical background and consistent design methodology in the area. Furthermore, it is quite difficult to implement really innovative and practically successful evolvable systems using contemporary digital reconfigurable technology.
Evolvable Hardware (Genetic and Evolutionary Computation #Vol. 11)
by Tetsuya Higuchi Xin YaoEvolvable hardware (EHW) refers to hardware whose architecture/structure and functions change dynamically and autonomously in order to improve its performance in carrying out tasks. The only single resource presenting both the fundamentals, and the latest advances in the field, this book teaches the basics of reconfigurable devices, why they are necessary and how they are designed.
Evolvable Hardware: From Practice to Application (Natural Computing Series)
by Martin A. Trefzer Andy M. TyrrellThis book covers the basic theory, practical details and advanced research of the implementation of evolutionary methods on physical substrates. Most of the examples are from electronic engineering applications, including transistor-level design and system-level implementation. The authors present an overview of the successes achieved, and the book will act as a point of reference for both academic and industrial researchers.
Evolvable Machines: Theory & Practice (Studies in Fuzziness and Soft Computing #161)
by Nadia Nedjah Luiza De Macedo MourelleMethods for the artificial evolution of active components, such as programs and hardware, are rapidly developing branches of adaptive computation and adaptive engineering. Evolvable Machines reports innovative and significant progress in automatic and evolutionary methodology applied to machine design. This book presents theoretical as well as practical chapters concentrating on Evolvable Robots, Evolvable Hardware Synthesis, as well as Evolvable Design.
Evolvable Systems: 8th International Conference, ICES 2008, Prague, Czech Republic, September 21-24, 2008, Proceedings (Lecture Notes in Computer Science #5216)
by Gregory S. Hornby Lukas Sekanina Pauline C. HaddowThis book constitutes the refereed proceedings of the 8th International Conference on Evolvable Systems, ICES 2008, held in Prague, Czech Republic, in September 2008. The 28 revised full papers and 14 revised poster papers presented were carefully reviewed and selected from 52 submissions. The papers are organized in topical sections on evolution of analog circuits, evolution of digital circuits, hardware-software codesign and platforms for adaptive systems, evolutionary robotics, development, real-world applications, evolutionary networking, evolvable artificial neural networks, and transistor-level circuit evolution.
Evolvable Systems: Third International Conference, ICES 2000, Edinburgh, Scotland, UK, April 17-19, 2000 Proceedings (Lecture Notes in Computer Science #1801)
by Julian F. Miller Adrian Thompson Peter Thomson Terence C. FogartyThis book constitutes the refereed proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware, ICES 2000, held in Edinburgh, Scotland, UK, in April 2000.The 27 revised full papers presented were carefully reviewed and selected for inclusion in the proceedings. Among the topics covered are evaluation of digital systems, evolution of analog systems, embryonic electronics, bio-inspired systems, artificial neural networks, adaptive robotics, adaptive hardware platforms, molecular computing, reconfigurable systems, immune systems, and self-repair.
Evolvable Systems: 6th International Conference, ICES 2005, Sitges, Spain, September 12-14, 2005, Proceedings (Lecture Notes in Computer Science #3637)
by J. Manuel Moreno Jordi Madrenas Jordi CospThe flying machines proposed by Leonardo da Vinci in the fifteenth century, the se- reproducing automata theory proposed by John von Neumann in the middle of the twentieth century and the current possibility of designing electronic and mechanical systems using evolutionary principles are all examples of the efforts made by humans to explore the mechanisms present in biological systems that permit them to tackle complex tasks. These initiatives have recently given rise to the emergent field of b- inspired systems and evolvable hardware. The inaugural workshop, Towards Evolvable Hardware, took place in Lausanne in October 1995, followed by the successive events of the International Conference on Evolvable Systems: From Biology to Hardware, held in Tsukuba (Japan) in October 1996, in Lausanne (Switzerland) in September 1998, in Edinburgh (UK) in April 2000, in Tokyo (Japan) in October 2001, and in Trondheim (Norway) in March 2003. Following the success of these past events the sixth international conference was aimed at presenting the latest developments in the field, bringing together researchers who use biologically inspired concepts to implement real systems in artificial intelligence, artificial life, robotics, VLSI design, and related domains. The sixth conference consolidated this biennial event as a reference meeting for the community involved in bio-inspired systems research. All the papers received were reviewed by at least three independent reviewers, thus guaranteeing a high-quality bundle for ICES 2005.