Bøger i IEEE Press Series on Computational Intelligence serien

An authoritative guide to computer simulation grounded in a multi-disciplinary approach for solving complex problemsSimulation and Computational Red Teaming for Problem Solving offers a review of computer simulation that is grounded in a multi-disciplinary approach. The authors present the theoretical foundations of simulation and modeling paradigms from the perspective of an analyst. The book provides the fundamental background information needed for designing and developing consistent and useful simulations. In addition to this basic information, the authors explore several advanced topics.The book's advanced topics demonstrate how modern artificial intelligence and computational intelligence concepts and techniques can be combined with various simulation paradigms for solving complex and critical problems. Authors examine the concept of Computational Red Teaming to reveal how the combined fundamentals and advanced techniques are used successfully for solving and testing complex real-world problems. This important book:* Demonstrates how computer simulation and Computational Red Teaming support each other for solving complex problems* Describes the main approaches to modeling real-world phenomena and embedding these models into computer simulations* Explores how a number of advanced artificial intelligence and computational intelligence concepts are used in conjunction with the fundamental aspects of simulationWritten for researchers and students in the computational modelling and data analysis fields, Simulation and Computational Red Teaming for Problem Solving covers the foundation and the standard elements of the process of building a simulation and explores the simulation topic with a modern research approach.

A thorough look at how societies can use cultural algorithms to understand human social evolutionFor those working in computational intelligence, developing an understanding of how cultural algorithms and social intelligence form the essential framework for the evolution of human social interaction is essential. This book, Cultural Algorithms: Tools to Model Complex Dynamic Social Systems, is the foundation of that study. It showcases how we can use cultural algorithms to organize social structures and develop socio-political systems that work.For such a vast topic, the text covers everything from the history of the development of cultural algorithms and the basic framework with which it was organized. Readers will also learn how other nature-inspired algorithms can be expressed and how to use social metrics to assess the performance of various algorithms.In addition to these topics, the book covers topics including:* The CAT system including the Repast Simphony System and CAT Sample Runs* How to problem solve using social networks in cultural algorithms with auctions* Understanding Common Value Action to enhance Social Knowledge Distribution Systems* Case studies on team formations* An exploration of virtual worlds using cultural algorithmsFor industry professionals or new students, Cultural Algorithms provides an impactful and thorough look at both social intelligence and how human social evolution translates into the modern world.

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation.

To aid in intelligent data mining, this book introduces a new family of unsupervised algorithms that have a basis in self-organization, yet are free from many of the constraints typical of other well known self-organizing architectures.

This book covers the hot topics and applications surrounding complex-valued neural networks. It demonstrates advanced theories with a wide range of applications, including optoelectronics systems, imaging systems, and remote sensing systems.

Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control.

Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems.

Lotfi Zadeh, the father of fuzzy logic, coined the phrase computing with words (CWW) to describe a methodology in which the computation objects are words drawn from a natural language.

This is the first self-contained book that covers the topic of Evolving Intelligent Systems in its entirety, from a systematic methodology to case studies and real industrial applications.

This book highlights the importance and recent success of computational intelligence methods over a diverse range of bioinformatics problems. It encourages others to use these methods and approaches in their research, while also serving as an introduction to computational intelligence methods and applications to the consumers of the research.

Written by two of the best-known experts in the field, Clustering is the only thoroughly comprehensive text on the subject currently available. The book looks at the full range of clustering and provides enough detail to allow users to select the method that best fits their application.

Explores both counter-terrorism and enabling policy dimensions of emerging information technologies in national security After the September 11th attacks, "connecting the dots" has become the watchword for using information and intelligence to protect the United States from future terrorist attacks.

Edited by a panel of experts, this book fills a gap in the existing literature by comprehensively covering system, processing, and application aspects of biometrics, based on a wide variety of biometric traits.

Soft computing is an emerging collection of methodologies that exploit tolerances for imprecision, uncertainty, and partial truth to achieve robustness, tractability, and low total cost. Hard computing solutions are usually more straightforward to analyze, and feature more predictable behavior and stability.

The rough and fuzzy set approaches presented here open up many new frontiers for continued research and development Computational Intelligence and Feature Selection provides readers with the background and fundamental ideas behind Feature Selection (FS), with an emphasis on techniques based on rough and fuzzy sets.

The revised and significantly expanded third edition of Evolutionary Computation presents the latest advances in the theory and practice of evolutionary computation. Highlighting the relationship between learning and intelligence, the book shows readers how to use simulated evolution to achieve machine intelligence.

ADP or Approximate Dynamic Programming has gone by many different names including: reinforcement learning (RL), adaptive critics (AC), and neuro-dynamic programming (NDP). The dynamic programming approach to decision and control problems involving nonlinear dynamic systems provides the optimal solution in any stochastic or uncertain environment.