Artificial Intelligence in the 21st Century PDF Download

Author: Stephen Lucci
Publisher: Mercury Learning and Information
ISBN: 1944534539
Category : Computers
Languages : en
Pages : 1168

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Book Description
This new edition provides a comprehensive, colorful, up-to-date, and accessible presentation of AI without sacrificing theoretical foundations. It includes numerous examples, applications, full color images, and human interest boxes to enhance student interest. New chapters on robotics and machine learning are now included. Advanced topics cover neural nets, genetic algorithms, natural language processing, planning, and complex board games. A companion DVD is provided with resources, applications, and figures from the book. Numerous instructors’ resources are available upon adoption. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. FEATURES: • Includes new chapters on robotics and machine learning and new sections on speech understanding and metaphor in NLP • Provides a comprehensive, colorful, up to date, and accessible presentation of AI without sacrificing theoretical foundations • Uses numerous examples, applications, full color images, and human interest boxes to enhance student interest • Introduces important AI concepts e.g., robotics, use in video games, neural nets, machine learning, and more thorough practical applications • Features over 300 figures and color images with worked problems detailing AI methods and solutions to selected exercises • Includes DVD with resources, simulations, and figures from the book • Provides numerous instructors’ resources, including: solutions to exercises, Microsoft PP slides, etc.

Author: S.. PANEERSELVAM SUMATHI (SUREKHA.)
Publisher: CRC Press
ISBN: 9780367384555
Category :
Languages : en
Pages : 851

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Book Description
Offering a wide range of programming examples implemented in MATLAB(R), Computational Intelligence Paradigms: Theory and Applications Using MATLAB(R) 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.

Author: Shayne Cox Gad
Publisher: John Wiley & Sons
ISBN: 0470249021
Category : Medical
Languages : en
Pages : 1352

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Book Description
A clear, straightforward resource to guide you through preclinical drug development Following this book's step-by-step guidance, you can successfully initiate and complete critical phases of preclinical drug development. The book serves as a basic, comprehensive reference to prioritizing and optimizing leads, dose formulation, ADME, pharmacokinetics, modeling, and regulations. This authoritative, easy-to-use resource covers all the issues that need to be considered and provides detailed instructions for current methods and techniques. Each chapter is written by one or more leading experts in the field. These authors, representing the many disciplines involved in preclinical toxicology screening and testing, give you the tools needed to apply an effective multidisciplinary approach. The editor has carefully reviewed all the chapters to ensure that each one is thorough, accurate, and clear. Among the key topics covered are: * Modeling and informatics in drug design * Bioanalytical chemistry * Absorption of drugs after oral administration * Transporter interactions in the ADME pathway of drugs * Metabolism kinetics * Mechanisms and consequences of drug-drug interactions Each chapter offers a full exploration of problems that may be encountered and their solutions. The authors also set forth the limitations of various methods and techniques used in determining the safety and efficacy of a drug during the preclinical stage. This publication should be readily accessible to all pharmaceutical scientists involved in preclinical testing, enabling them to perform and document preclinical safety tests to meet all FDA requirements before clinical trials may begin.

Author: Anthony Brabazon
Publisher: Springer
ISBN: 3662436310
Category : Computers
Languages : en
Pages : 554

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Book Description
The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.

Author: Charles Dierbach
Publisher:
ISBN: 9788126556014
Category :
Languages : en
Pages : 580

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Book Description

Author: Alexander O. Tarakanov
Publisher: Springer Science & Business Media
ISBN: 9780387955339
Category : Computers
Languages : en
Pages : 216

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Book Description
Overview This book introduces immunocomputing (Ie) as a new computing approach that replicates the principles of information processing by proteins and immune networks. It establishes a rigorous mathematical basis for IC, consistent with recent findings in immunology, and it presents various applications of IC to specific computationally intensive real-life problems. The hardware implementation aspects of the IC concept in an immunocomputer as a new kind of computing medium and its potential connections with modem biological microchips (biochips) and future biomolecular computers (biocomputers) are also discussed. All biological systems at the cellular and biomolecular levels are sophisticated mechanisms honed to perfection by millions of years of evolution, and their exploration provides inspiration for various novel concepts in science and engineering. Of these systems, however, only two types, the neural system and the immune system of the vertebrates, possess the extraordinary capabilities of "intellectual" information processing, which include memory, the ability to learn, to recognize, and to make decisions with respect to unknown situations. The potential of the natural neural system as a biological prototype of a computing scheme has already been utilized intensively in computer science through the mathematical and software models of artificial neural networks (ANN) and their hardware implementation in neural computers (see, e.g., Haykin, 1999; Wasserman, 1990).

Author: Leandro Nunes de Castro
Publisher: Springer Science & Business Media
ISBN: 1852335947
Category : Computers
Languages : en
Pages : 380

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Book Description
Artificial Immune Systems (AIS) are adaptive systems inspired by the biological immune system and applied to problem solving. This book provides an accessible introduction that will be suitable for anyone who is beginning to study or work in this area. It gives a clear definition of an AIS, sets out the foundations of the topic (including basic algorithms), and analyses how the immune system relates to other biological systems and processes. No prior knowledge of immunology is needed - all the essential background information is covered in the introductory chapters. Key features of the book include: - A discussion of AIS in the context of Computational Intelligence; - Case studies in Autonomous Navigation, Computer Network Security, Job-Shop Scheduling and Data Analysis =B7 An extensive survey of applications; - A framework to help the reader design and understand AIS; - A web site with additional resources including pseudocodes for immune algorithms, and links to related sites. Written primarily for final year undergraduate and postgraduate students studying Artificial Intelligence, Evolutionary and Biologically Inspired Computing, this book will also be of interest to industrial and academic researchers working in related areas.

Author: Omid Bozorg-Haddad
Publisher: John Wiley & Sons
ISBN: 1119386993
Category : Mathematics
Languages : en
Pages : 306

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Book Description
A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.

Author: S. Sumathi
Publisher: CRC Press
ISBN: 1498743722
Category : Technology & Engineering
Languages : en
Pages : 731

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Book Description
Considered one of the most innovative research directions, computational intelligence (CI) embraces techniques that use global search optimization, machine learning, approximate reasoning, and connectionist systems to develop efficient, robust, and easy-to-use solutions amidst multiple decision variables, complex constraints, and tumultuous environments. CI techniques involve a combination of learning, adaptation, and evolution used for intelligent applications. Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® explores the performance of CI in terms of knowledge representation, adaptability, optimality, and processing speed for different real-world optimization problems. Focusing on the practical implementation of CI techniques, this book: Discusses the role of CI paradigms in engineering applications such as unit commitment and economic load dispatch, harmonic reduction, load frequency control and automatic voltage regulation, job shop scheduling, multidepot vehicle routing, and digital image watermarking Explains the impact of CI on power systems, control systems, industrial automation, and image processing through the above-mentioned applications Shows how to apply CI algorithms to constraint-based optimization problems using MATLAB® m-files and Simulink® models Includes experimental analyses and results of test systems Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® provides a valuable reference for industry professionals and advanced undergraduate, postgraduate, and research students.

Author: Pranee Liamputtong
Publisher: Cambridge University Press
ISBN: 1139487647
Category : Social Science
Languages : en
Pages : 303

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Book Description
Cross-cultural research is rife with ethical and methodological challenges but, despite the increased demand for such research, discussions on 'culturally sensitive methodologies' are still largely neglected. Consequently, researchers often find themselves faced with difficulties but lack information on how to deal with them. This text provides an in-depth discussion on how to perform qualitative research in cross-cultural contexts with an emphasis on a more ethical, sensible and responsible approach. Pranee Liamputtong suggests culturally sensitive and appropriate research methods that would work well with cultural groups. She offers thought-provoking perspectives and diverse cultural examples which will be of value to both novice and experienced cross-cultural researchers. Throughout the volume there are references to the excellent work of many cross-cultural researchers who have paved the way in different social and cultural settings.