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Evolutionary programming

Most popular at the top

  • Analyzing Evolutionary Algorithmsby Thomas Jansen

    Springer 2012; US$ 109.00

    Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years.  In this book the author provides an introduction to the methods used to analyze evolutionary algorithms... more...

  • Genetic and Evolutionary Computingby Jang-Shyang Pan

    Springer International Publishing 2013; US$ 259.00

    Genetic and Evolutionary Computing This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at ICGEC 2013, the 7th International Conference on Genetic and Evolutionary Computing. The conference this year was technically co-sponsored by The Waseda University in Japan, Kaohsiung University of Applied Science in... more...

  • Prior Processes and Their Applicationsby Eswar G. Phadia

    Springer Berlin Heidelberg 2013; US$ 79.99

    This book presents a systematic and comprehensive treatment of various prior processes that have been developed over the last four decades in order to deal with the Bayesian approach to solving some nonparametric inference problems. Applications of these priors in various estimation problems are presented. Starting with the famous Dirichlet process... more...

  • A Brief Introduction to Continuous Evolutionary Optimizationby Oliver Kramer

    Springer International Publishing 2013; US$ 54.99

    This book introduces heuristics and algorithms for black box optimization with evolutionary algorithms in continuous solution spaces. It presents heuristic extensions that allow optimization in constrained, multimodal and multi-objective solution spaces. more...

  • Bayesian Modelsby N. Thompson Hobbs; Mevin B. Hooten

    Princeton University Press 2015; US$ 49.50

    Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods?in language ecologists can understand. Unlike other books on the subject, this one emphasizes... more...

  • Current Trends in Bayesian Methodology with Applicationsby Satyanshu K. Upadhyay; Umesh Singh; Dipak K. Dey; Appaia Loganathan

    CRC Press 2015; US$ 99.95

    Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation,... more...

  • Field-Based Coordination for Pervasive Multiagent Systemsby Marco Mamei; Franco Zambonelli

    Springer Berlin Heidelberg 2006; US$ 179.00

    More and more, software systems involve autonomous and distributed software components that have to execute and interact in open and dynamic environments, such as in pervasive, autonomous, and mobile applications. The requirements with respect to dynamics, openness, scalability, and decentralization call for new approaches to software design and development,... more...

  • Handbook of Bioinspired Algorithms and Applicationsby Stephan Olariu; Albert Y. Zomaya

    CRC Press 2005; US$ 194.95

    The mystique of biologically inspired (or bioinspired) paradigms is their ability to describe and solve complex relationships from intrinsically very simple initial conditions and with little or no knowledge of the search space. Edited by two prominent, well-respected researchers, the Handbook of Bioinspired Algorithms and Applications reveals the... more...

  • Parameter Setting in Evolutionary Algorithmsby Fernando G. Lobo; Claudio F. Lima; Zbigniew Michalewicz

    Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2007; US$ 159.00

    One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation... more...

  • Evolutionary Schedulingby Keshav Dahal; Kay Chen Tan; Peter I. Cowling

    Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2007; US$ 169.00

    Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. This book gives an overview of the developments in the growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems. more...