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Computation and Intelligence,Collected Readings
Computation and Intelligence brings together 29 readings in Artificial Intelligence that are particularly relevant to today's student/practitioner. With its helpful critique of the selections, extensive bibliography, and clear presentation of the material, Computation and Intelligence will be a useful adjunct to any course in AI as well as a handy reference for professionals in the field. The book is divided into five parts, each reflecting the stages of development of AI. The first part, Foundations,, contains readings that present or discuss foundational ideas linking computation and intelligence, typified by A. M. Turing's "Computing Machinery and Intelligence." The second part, Knowledge Representation, presents a sampling of numerous representational schemes by Newell, Minsky, Collins & Quillian, Winograd, Schank, Hayes, Holland, McClelland, Rumelhart, Hinton, and Brooks. The third part, Weak Method Problem Solving, fouses on the research and design of syntax-based problem solvers, including the most famous of these, the Logic Theorist and GPS. The fourth part, Reasoning in Complex and Dynamic Environments, presents a broad spectrum of the AI community's research in knowledge-intensive problem solving, from McCarthy's early design of systems with "common sense" to model-based reasoning. The two concluding selections, by Marvin Minsky and by Herbert Simon, respectively, present the recent thoughts of two of AI's pioneers who revisit the concepts and controversies that have developed during the evolution of the tools and techniques that make up the current practice of Artificial Intelligence.
by George F. Luger
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Computational Intelligence,Concepts to Implementations
The "soft" analytic tools that comprise the field of computational intelligence have matured to the extent that they can, often in powerful combination with one another, form the foundation for a variety of solutions suitable for use by domain experts without extensive programming experience. Computational Intelligence: Concepts to Implementations provides the conceptual and practical knowledge necessary to develop solutions of this kind. Focusing on evolutionary computation, neural networks, and fuzzy logic, the authors have constructed an approach to thinking about and working with computational intelligence that has, in their extensive experience, proved highly effective. Russ Eberhart and Yuhui Shi have succeeded in integrating various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook, including lots of practical examples. -Shun-ichi Amari, RIKEN Brain Science Institute, Japan This book is an excellent choice on its own, but, as in my case, will form the foundation for our advanced graduate courses in the CI disciplines. -James M. Keller, University of Missouri-Columbia The excellent new book by Eberhart and Shi asserts that computational intelligence rests on a foundation of evolutionary computation. This refreshing view has set the book apart from other books on computational intelligence. The book has an emphasis on practical applications and computational tools, which are very useful and important for further development of the computational intelligence field. -Xin Yao, The Centre of Excellence for Research in Computational Intelligence and Applications, Birmingham Moves clearly and efficiently from concepts and paradigms to algorithms and implementation techniques by focusing, in the early chapters, on the specific concepts and paradigms that inform the authors' methodologies Explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation Details the metrics and analytical tools needed to assess the performance of computational intelligence tools Concludes with a series of case studies that illustrate a wide range of successful applications Presents code examples in C and C++ Provides, at the end of each chapter, review questions and exercises suitable for graduate students, as well as researchers and practitioners engaged in self-study Makes available, on a companion website, a number of software implementations that can be adapted for real-world applications
by Russell C. Eberhart
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Computational Intelligence,An Introduction
by Andries P. Engelbrecht
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Advances in Computation and Intelligence,5th International Symposium, ISICA 2010, Wuhan, China, October 22-24, 2010, Proceedings
Kang, Zhuo Book jacket.
by Jingnan Liu
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Computational Intelligence Paradigms,Theory & Applications using MATLAB
Offering a wide range of programming examples implemented in MATLAB®, Computational Intelligence Paradigms: Theory and Applications Using MATLAB® presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research. The book first focuses on neural networks, including common artificial neural networks; neural networks based on data classification, data association, and data conceptualization; and real-world applications of neural networks. It then discusses fuzzy sets, fuzzy rules, applications of fuzzy systems, and different types of fused neuro-fuzzy systems, before providing MATLAB illustrations of ANFIS, classification and regression trees, fuzzy c-means clustering algorithms, fuzzy ART map, and Takagi–Sugeno inference systems. The authors also describe the history, advantages, and disadvantages of evolutionary computation and include solved MATLAB programs to illustrate the implementation of evolutionary computation in various problems. After exploring the operators and parameters of genetic algorithms, they cover the steps and MATLAB routines of genetic programming. The final chapter introduces swarm intelligence and its applications, particle swarm optimization, and ant colony optimization. Full of worked examples and end-of-chapter questions, this comprehensive book explains how to use MATLAB to implement CI techniques for the solution of biological problems. It will help readers with their work on evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and the evolution of social behaviors.
by S. Sumathi
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Advances in Computation and Intelligence,4th International Symposium on Intelligence Computation and Applications, ISICA 2009, Huangshi, China, October 23-25, 2009, Proceedings
VolumesofLNCS 5821andCCIS51aretheproceedingsofthe 4thInternational Symposium on Intelligence Computation and Applications (ISICA 2009) held in Huangshi, China, October 23–25, 2009. These two volumes are in memory of Prof. Lishan Kang, the ISICA 2009 Honorary General Chair, who was a leading ?gurein the ?elds of domain decomposition methods and computational intelligence. ISICA 2009 successfully attracted over 300 submissions. Through rigorous reviews, 58 high-quality papers were included in LNCS 5821, while the other 54 papers were collected in CCIS 51. ISICA conferencesare one of the ?rst series of internationalconferencesoncomputationalintelligencethatcombineelementsof learning, adaptation, evolution and fuzzy logic to create programsas alternative solutions to arti?cial intelligence. The last three ISICA proceedings have been accepted in the Index to Scienti?c and Technical Proceedings (ISTP) and/or Engineering Information (EI). Following the success of the past three ISICA events, ISICA 2009 made good progress in the analysis and design of newly developed methods in the ?eld of computationalintelligence. ISICA 2009featured the most up-to-dateresearchin analysisandtheoryofevolutionaryalgorithms,neuralnetworkarchitecturesand learning, fuzzy logic and control, predictive modeling for robust classi?cation, swarm intelligence, evolutionary system design, evolutionary image analysis and signal processing, and computational intelligence in engineering design. ISICA 2009 provided a venue to foster technical exchanges, renew everlasting frie- ships, and establish new connections.
by Zhihua Cai
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Advances in Computation and Intelligence,Third International Symposium on Intelligence Computation and Applications, ISICA 2008 Wuhan, China, December 19-21, 2008 Proceedings
We are proud to introduce the proceedings of the Third International Sym- sium on Intelligence Computation and Applications (ISICA 2008) held at the China UniversityofGeosciences(Wuhan), China,during December 19–21,2008. ISICA 2008 successfully attracted nearly 700 submissions. Through rigorous - views, 93 high-quality papers were included in the proceedings of ISICA 2008. ISICA conferences are one of the ?rst series of internationalconferences on c- putational intelligence that combine elements of learning, adaptation, evolution and fuzzy logic to create programs as alternative solutions to arti?cial intel- gence. The proceedings of ISICA conferences have a number of special features including uniqueness, novelty, success, and broadness of scope. The proceedings ofISICA conferences havebeen acceptedin the Index to Scienti?c andTechnical Proceedings (ISTP), while the ISICA 2007 proceedings have also been indexed by Engineering Information (EI). Following the success of ISICA 2005 and ISICA 2007, ISICA 2008 made good progress on analyzing and processing massive real-time data by compu- tional intelligence. ISICA 2008 featured the most up-to-date research in c- putational intelligence, evolutionary computation, evolutionary multi-objective and dynamic optimization,evolutionarylearning systems, neuralnetworks,cl- si?cation and recognition, bioinformatics and bioengineering, evolutionary data mining and knowledge discovery, intelligent GIS and control, theory of int- ligent computation, combinational and numerical optimization, and real-world applications. ISICA 2008 provided a venue to foster technical exchanges, renew everlasting friendships, and establish new connections.
by Lishan Kang
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Artificial Immune Systems: A New Computational Intelligence Approach,
Recently there has been a growing interest in the use of the biological immune system as a source of inspiration for solving complicated computational problems. The immune system involves many information-processing abilities including pattern recognition, learning, memory and inherent distributed parallel processing and for these, and other reasons, it has received a significant amount of interest as a metaphor within computing. This emerging field is known as Artificial Immune Systems (AIS), and applications of AIS include, machine learning, fault diagnosis, computer security, scheduling, virus detection and optimisation.
by Leandro Nunes de Castro
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Artificial Intelligence,Foundations of Computational Agents
Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This textbook, aimed at junior to senior undergraduate students and first-year graduate students, presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents. By showing how basic approaches fit into a multidimensional design space, readers can learn the fundamentals without losing sight of the bigger picture. The book balances theory and experiment, showing how to link them intimately together, and develops the science of AI together with its engineering applications. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers, and independent learners. AI is a rapidly developing field: this book encapsulates the latest results without being exhaustive and encyclopedic. The text is supported by an online learning environment, AIspace, http://aispace.org, so that students can experiment with the main AI algorithms plus problems, animations, lecture slides, and a knowledge representation system, AIlog, for experimentation and problem solving.
by David L. Poole
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Artificial Intelligence and Symbolic Computation,8th International Conference, AISC 2006, Beijing, China, September 20-22, 2006, Proceedings
AISC 2006, the 8th International Conference on Arti?cial Intelligence and S- bolic Computation,was held onthe campus ofBeihang University,China,in the golden autumn of 2006. On behalf of the Organizing Committee and Beihang University,Ihadthepleasuretowelcometheparticipantsofthis conference.The AISC series of specialized biennial conferences was founded in 1992 by Jacques Calmet and John Campbell with initial title “Arti?cial Intelligence and S- bolic Mathematical Computing†(AISMC) and the previous seven conferences in this series were held in Karlsruhe (AISMC-1, 1992), Cambridge (AISMC-2, 1994), Steyr (AISMC-3, 1996), Plattsburgh, NY (AISC 1998), Madrid (AISC 2000), Marseille (AISC 2002), and Hagenberg, Austria (AISC 2004). Arti?cialintelligenceandsymboliccomputationaretwoviewsandapproaches for automating (mathematical) problem solving. They are based on heuristics and mathematical algorithmics, respectively, and each of them can be applied to the other. The AISC series of conferences has not only provided a lively forum for researchers to exchange ideas and views and to present work and new ?ndings, but has also stimulated the development of theoretical insights and results, practical methods and algorithms, and advanced tools of software technology and system design in the interaction of the two ?elds and research communities, meanwhile leading to a broad spectrum of applications by the combined problem solving power of the two ?elds.
by Jaques Calmet
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Fundamentals of Computational Swarm Intelligence,
Fundamentals of Computational Swarm Intelligence provides a comprehensive introduction to the new computational paradigm of Swarm Intelligence (SI), a field that emerged from biological research, and is now picking up momentum within the computational research community. Bio-inspired systems are becoming increasingly important research areas for computer scientists, engineers, economists, bioinformaticians, operational researchers, and many other disciplines. This book introduces the reader to the mathematical models of social insects collective behaviour, and shows how they can be used in solving optimization problems. Focusing on the algorithmic implementation of models of swarm behavior, this book: Examines how social network structures are used to exchange information among individuals, and how the aggregate behaviour of these individuals forms a powerful organism. Introduces a compact summary of the formal theory of optimisation. Outlines paradigms with relations to SI, including genetic algorithms, evolutionary programming, evolutionary strategies, cultural algorithms and co-evolution. Looks at the choreographic movements of birds in a flock as a basis for the Particle Swarm Optimization (PSO) models, and provides an extensive treatment of different classes of PSO models. Shows how the behaviour of ants can be used to implement Ant Colony Optimization (ACO) algorithms to solve real-world problems including routing optimization, structure optimization, data mining and data clustering. Considers different classes of optimization problems, including multi-objective optimization, dynamic environments, discrete and continuous search spaces, constrained optimization, and niching. Includes an accompanying website containing Java classes and implementations of the different algorithms that can be used to test PSO and ACO algorithms: http://si.cs.up.ac.za The interdisciplinary nature of this field will make Fundamentals of Computational Swarm Intelligence an essential resource for readers with diverse backgrounds. In addition, it will be an excellent reference for computer scientists, practitioners in business or industry and researchers involved in the analysis, design and simulation of multibody systems. Advanced undergraduates and graduate students in artificial intelligence, collective intelligence and engineering will also find this book an invaluable tool.
by Andries P. Engelbrecht
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Computational Intelligence in Automotive Applications,
The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence - quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, confectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automate, self-organizing systems, soft computing, fuzzy systems and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.
by Danil Prokhorov
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Artificial intelligence in scientific computation,towards second generation systems
by Rafael M. Huber
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Evolutionary Computation,Toward a New Philosophy of Machine Intelligence
This Third Edition provides the latest tools and techniques that enable computers to learn The Third Edition of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does. Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers. As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation. The Third Edition also features new knowledge-building aids. Readers will find a host of new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well. This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook.
by David B. Fogel
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Intelligence Computation and Evolutionary Computation,Results of 2012 International Conference of Intelligence Computation and Evolutionary Computation ICEC 2012 Held July 7, 2012 in Wuhan, China
2012 International Conference of Intelligence Computation and Evolutionary Computation (ICEC 2012) is held on July 7, 2012 in Wuhan, China. This conference is sponsored by Information Technology & Industrial Engineering Research Center. ICEC 2012 is a forum for presentation of new research results of intelligent computation and evolutionary computation. Cross-fertilization of intelligent computation, evolutionary computation, evolvable hardware and newly emerging technologies is strongly encouraged. The forum aims to bring together researchers, developers, and users from around the world in both industry and academia for sharing state-of-art results, for exploring new areas of research and development, and to discuss emerging issues facing intelligent computation and evolutionary computation.
by Zhenyu Du
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