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Nature Inspired Problem-Solving Methods in Knowledge Engineering ; 2nd International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part II
The second of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007.
Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)
The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.
Natural computing in computational finance
Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance.
Multiobjective Problem Solving from Nature : From Concepts to Applications
he book focuses on how MOEAs and related techniques can be used to solve problems, particularly in the disciplines of science and engineering. Contributions by leading researchers show how the concepts of multiobjective optimization can be used to reformulate and resolve problems in broad areas such as constrained optimization, coevolution, classification, inverse modelling and design. The book is distinguished from other texts on MOEAs in that it is not primarily about the algorithms, nor specific applications, but about the concepts and processes involved in solving problems using a multiobjective approach. Each chapter contributes to the central, deep concepts and themes of the book: evaluating the utility of the multiobjective approach; discussing alternative problem formulations; showing how problem formulation affects the search process; and examining solution selection and decision making.
Multiobjective Optimization : Interactive and Evolutionary Approaches
Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support.
Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases
The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.
Multiobjective Evolutionary Algorithms and Applications
Multiobjective Evolutionary Algorithms and Applications provides comprehensive treatment on the design of multiobjective evolutionary algorithms and their applications in domains covering areas such as control and scheduling. Emphasizing both the theoretical developments and the practical implementation of multiobjective evolutionary algorithms, a profound mathematical knowledge is not required. Written for a wide readership, engineers, researchers, senior undergraduates and graduate students interested in the field of evolutionary algorithms and multiobjective optimization with some basic knowledge of evolutionary computation will find this book a useful addition to their book case.
Multidisciplinary Methods for Analysis, Optimization and Control of Complex Systems
Consists of lecture notes of a summer school named after the late Jacques Louis Lions. The summer school was designed to alert both Academia and Industry to the increasing role of multidisciplinary methods and tools for the design of complex products in various areas of socio-economic interest.
Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems : From Analytical to Soft Computing Approaches
This monograph presents a variety of techniques that can be used for designing robust fault diagnosis schemes for non-linear systems. The introductory part of the book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. Subsequently, advanced robust observer structures are presented. Parameter estimation based techniques are discussed as well. A particular attention is drawn to experimental design for fault diagnosis. The book also presents a number of robust soft computing approaches utilizing evolutionary algorithms and neural networks. All approaches described in this book are illustrated by practical applications.
MICAI 2006 : Advances in Artificial Intelligence ; 5th Mexican International Conference on Artificial Intelligence, Apizaco, Mexico, November 13-17, 2006, Proceedings
This volume contains the papers presented during the oral session of the 5 Mexican International Conference on Artificial Intelligence, held on November 13–17, 2006, at the Technologic Institute of Apizaco, Mexico. The conference received for evaluation 448 submissions by 1207 authors from 42 different countries
Metaheuristics for Scheduling in Industrial and Manufacturing Applications
This book deals with the application of various novel metaheuristics in scheduling. Addressing the various issues of scheduling in industrial and manufacturing applications is the novelty of this edited volume. Important features include the detailed overview of the various novel metaheuristic scheduling approaches, excellent coverage of timely, advanced scheduling topics, state-of-the-art theoretical research and application developments and chapters authored by pioneers in the field.
Metaheuristics for Hard Optimization : Methods and Case Studies
Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the detailed presentation of the four most widely known metaheuristics: the simulated annealing method, tabu search, the evolutionary algorithms, and ant colony algorithms. Each one of these metaheuristics is actually a family of methods, of which the essential elements are discussed. In the second part, the book presents some other less widespread metaheuristics, then, extensions of metaheuristics and some ways of research are described . The problem of the choice of a metaheuristic is posed and solution methods are discussed. The last part concentrates on three case studies from telecommunications, air traffic control, and vehicle routing.
Mechanisms, Symbols, and Models Underlying Cognition ; 1st International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part I
Constitute the refereed proceedings of the First International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2005. This two-volume set contains papers that are related with the conceptual developments in the fields of Neurophysiology and cognitive science, and also to bioinspired programming strategies.
Intelligent data engineering and automated Learning - IDEAL 2008 ; 9th International Conference Daejeon, South Korea, November 2-5, 2008 Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2008, held in Daejeon, Korea, in November 2008.The 56 revised full papers presented together with 10 invited papers were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers are organized in topical sections on learning and information processing, data mining and information management, bioinformatics and neuroinformatics, agents and distributed systems, as well as financial engineering and modeling.
Intelligent Computing Theories and Application ; 17th International Conference, ICIC 2021, Shenzhen, China, August 12–15, 2021, Proceedings, Part I
The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.”
Intelligent Computing ; International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006, Proceedings, Part I
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum with dedication to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring together researchers and practitioners from both the academia and industry to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing. The ICIC 2006 to be held in Kunming, Yunnan, China, 16-19 August 2006 is the second International Conference on Intelligent Computing, which is built upon the success of ICIC 2005 held in Hefei, China, 2005. This year, the conference mainly concentrates on the theories & methodologies as well as the emerging applications of intelligent computing. It intends to unify the contemporary intelligent computing techniques within an integral framework that highlights the trends in advanced computational intelligence and bridges the theoretical research with the applications. In particular, the bio-inspired computing emerges as a key role in pursuing for novel technology in recently years. The resulting techniques vitalize the life science engineering and daily life applications. In light of this trend, the theme for this conference is the Emerging Intelligent Computing Technology and Applications. Papers related to this theme were especially solicited, including theories, methodologies, and applications in science and technology.
Innovations in Intelligent Machines - 1
This book includes a collection of chapters on the state of art in the area of intelligent machines. This research would provide a sound basis to make autonomous systems human-like. The contributions include: An introduction to intelligent machines / Supervisory control of multiple UAVs / Intelligent autonomous UAV task allocation / UAV path planning / Dynamic path planning / Routing in UAVS State estimation of micro air vehicles / Architecture for soccer playing robots / Robot perception / Application engineers scientists and researchers will find this book useful.
Information Processing with Evolutionary Algorithms : From Industrial Applications to Academic Speculations
The last decade of the 20th century has witnessed a surge of interest in num- ical, computation-intensive approaches to information processing. The lines that draw the boundaries among statistics, optimization, arti cial intelligence and information processing are disappearing, and it is not uncommon to nd well-founded and sophisticated mathematical approaches in application - mains traditionally associated with ad-hoc programming. Heuristics has - come a branch of optimization and statistics. Clustering is applied to analyze soft data and to provide fast indexing in the World Wide Web. Non-trivial matrix algebra is at the heart of the last advances in computer vision. The breakthrough impulse was, apparently, due to the rise of the interest in arti cial neural networks, after its rediscovery in the late 1980s. Disguised as ANN, numerical and statistical methods made an appearance in the - formation processing scene, and others followed. A key component in many intelligent computational processing is the search for an optimal value of some function. Sometimes, this function is not evident and it must be made explicit in order to formulate the problem as an optimization problem. The search - ten takes place in high-dimensional spaces that can be either discrete, or c- tinuous or mixed. The shape of the high-dimensional surface that corresponds to the optimized function is usually very complex. Evolutionary algorithms are increasingly being applied to information processing applications that require any kind of optimization.
Information Processing in Medical Imaging ; 20th International Conference, IPMI 2007, Kerkrade, The Netherlands, July 2-6, 2007, Proceedings
The 20th International Conference on Information Processing in Medical Im- ing(IPMI)washeldduringJuly2–6,2007,atRolducAbbey,locatedinKerkrade in the south of the Netherlands. IPMI is one of the longest running conferences in medical imaging.
Hybrid metaheuristics ; Vol. 4030 ; 3rd International Workshop, HM 2006, Gran Canaria, Spain, October 13-14, 2006, Proceedings
The selection of papers for HM 2006 consolidated some of the mainstream issues that have emerged from the past editions. Firstly, there are prominent examples of e?ective hybrid techniques whose design and implementation were motivated by challenging real-world applications. We believe this is particularly important for two reasons: on the one hand, researchers are conscious that the primary goal of developing algorithms is to solve relevant real-life problems; on the other hand, the path towarde?cient solving methods for practical problems is a source of new outstanding ideas and theories. A second important issue is that the research community on metaheur- tics has become increasingly interested in and open to techniques and methods known from arti?cial intelligence (AI) and operations research (OR). So far, the most representative examples of such integration have been the use of AI/OR techniques as subordinates of metaheuristic methods. As a historical and - ymological note, this is in perfect accordance with the original meaning of a metaheuristic as a “general strategy controlling a subordinate heuristic. ” The awareness of the need for a sound experimental methodology is a third keypoint.
