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Evolutionary Algorithms For Solving Multi-Objective Problems

by Carlos Coello Coello, David A. Van Veldhuizen e Gary B. Lamont

~~95,40€~~ 76,32€ 20% OFF + 5% CARD

 Researchers and practitioners alike are increasingly turning to search, op timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solv ing problems and inventing new hardware and software that rival human designs. The Kluwer Series on Genetic Algorithms and Evolutionary Computation pub lishes research monographs, edited collections, and graduate-level texts in this rapidly growing field. Primary areas of coverage include the theory, implemen tation, and application of genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), learning classifier systems (LCSs) and other variants of genetic and evolutionary computation (GEC). The series also pub lishes texts in related fields such as artificial life, adaptive behavior, artificial immune systems, agent-based systems, neural computing, fuzzy systems, and quantum computing as long as GEC techniques are part of or inspiration for the system being described. This encyclopedic volume on the use of the algorithms of genetic and evolu tionary computation for the solution of multi-objective problems is a landmark addition to the literature that comes just in the nick of time. Multi-objective evolutionary algorithms (MOEAs) are receiving increasing and unprecedented attention. Researchers and practitioners are finding an irresistible match be tween the popUlation available in most genetic and evolutionary algorithms and the need in multi-objective problems to approximate the Pareto trade-off curve or surface.
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Efficient And Accurate Parallel Genetic Algorithms

by Erick Cantu-Paz

~~118,59€~~ 94,87€ 20% OFF + 5% CARD

 As genetic algorithms (GAs) become increasingly popular, they are applied to difficult problems that may require considerable computations. In such cases, parallel implementations of GAs become necessary to reach high-quality solutions in reasonable times. But, even though their mechanics are simple, parallel GAs are complex non-linear algorithms that are controlled by many parameters, which are not well understood. Efficient and Accurate Parallel Genetic Algorithms is about the design of parallel GAs. It presents theoretical developments that improve our understanding of the effect of the algorithm''s parameters on its search for quality and efficiency. These developments are used to formulate guidelines on how to choose the parameter values that minimize the execution time while consistently reaching solutions of high quality. Efficient and Accurate Parallel Genetic Algorithms can be read in several ways, depending on the readers'' interests and their previous knowledge about these algorithms. Newcomers to the field will find the background material in each chapter useful to become acquainted with previous work, and to understand the problems that must be faced to design efficient and reliable algorithms. Potential users of parallel GAs that may have doubts about their practicality or reliability may be more confident after reading this book and understanding the algorithms better. Those who are ready to try a parallel GA on their applications may choose to skim through the background material, and use the results directly without following the derivations in detail. These readers will find that using the results can help them to choose the type of parallel GA that best suits their needs, without having to invest the time to implement and test various options. Once that is settled, even the most experienced users dread the long and frustrating experience of configuring their algorithms by trial and error. The guidelines contained herein will shorten dramatically the time spent tweaking the algorithm, although some experimentation may still be needed for fine-tuning. Efficient and Accurate Parallel Genetic Algorithms is suitable as a secondary text for a graduate level course, and as a reference for researchers and practitioners in industry.
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Estimation Of Distribution Algorithms - A New Tool For Evolutionary Computation

~~237,84€~~ 190,27€ 20% OFF + 5% CARD

 A New Tool for Evolutionary Computation.
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Noisy Optimization With Evolution Strategies

by Dirk V. Arnold

~~118,59€~~ 94,87€ 20% OFF + 5% CARD

 Noise is a common factor in most real-world optimization problems. Sources of noise can include physical measurement limitations, stochastic simulation models, incomplete sampling of large spaces, and human-computer interaction. Evolutionary algorithms are general, nature-inspired heuristics for numerical search and optimization that are frequently observed to be particularly robust with regard to the effects of noise.Noisy Optimization with Evolution Strategies contributes to the understanding of evolutionary optimization in the presence of noise by investigating the performance of evolution strategies, a type of evolutionary algorithm frequently employed for solving real-valued optimization problems. By considering simple noisy environments, results are obtained that describe how the performance of the strategies scales with both parameters of the problem and of the strategies considered. Such scaling laws allow for comparisons of different strategy variants, for tuning evolution strategies for maximum performance, and they offer insights and an understanding of the behavior of the strategies that go beyond what can be learned from mere experimentation.This first comprehensive work on noisy optimization with evolution strategies investigates the effects of systematic fitness overvaluation, the benefits of distributed populations, and the potential of genetic repair for optimization in the presence of noise. The relative robustness of evolution strategies is confirmed in a comparison with other direct search algorithms.Noisy Optimization with Evolution Strategies is an invaluable resource for researchers and practitioners of evolutionary algorithms.
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Omega - A Competent Genetic Algorithm For Solving Permutation And Scheduling Problems

by Dimitri Knjazew

~~118,59€~~ 94,87€ 20% OFF + 5% CARD

 A Competent Genetic Algorithm for Solving Permutation and Scheduling Problems.
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Design Of Innovation - Lessons From And For Competent Genetic Algorithms

by David E. Goldberg

~~59,61€~~ 47,69€ 20% OFF + 5% CARD

 7 69 6 A DESIGN APPROACH TO PROBLEM DIFFICULTY 71 1 Design and Problem Difficulty 71 2 Three Misconceptions 72 3 Hard Problems Exist 76 4 The 3-Way Decomposition and Its Core 77 The Core of Intra-BB Difficulty: Deception 5 77 6 The Core of Inter-BB Difficulty: Scaling 83 7 The Core of Extra-BB Difficulty: Noise 88 Crosstalk: All Roads Lead to the Core 8 89 9 From Multimodality to Hierarchy 93 10 Summary 100 7 ENSURING BUILDING BLOCK SUPPLY 101 1 Past Work 101 2 Facetwise Supply Model I: One BB 102 Facetwise Supply Model II: Partition Success 103 3 4 Population Size for BB Supply 104 Summary 5 106 8 ENSURING BUILDING BLOCK GROWTH 109 1 The Schema Theorem: BB Growth Bound 109 2 Schema Growth Somewhat More Generally 111 3 Designing for BB Market Share Growth 112 4 Selection Press ure for Early Success 114 5 Designing for Late in the Day 116 The Schema Theorem Works 6 118 A Demonstration of Selection Stall 7 119 Summary 122 8 9 MAKING TIME FOR BUILDING BLOCKS 125 1 Analysis of Selection Alone: Takeover Time 126 2 Drift: When Selection Chooses for No Reason 129 3 Convergence Times with Multiple BBs 132 4 A Time-Scales Derivation of Critical Locus 142 5 A Little Model of Noise-Induced Run Elongation 143 6 From Alleles to Building Blocks 147 7 Summary 148 10 DECIDING WELL 151 1 Why is Decision Making a Problem? 151
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Evolutionary Algorithms For Embedded System Design

~~118,59€~~ 94,87€ 20% OFF + 5% CARD

 Evolutionary Algorithms for Embedded System Design describes how Evolutionary Algorithm (EA) concepts can be applied to circuit and system design - an area where time-to-market demands are critical.
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Evolutionary Optimization In Dynamic Environments

by Jurgen Branke

~~237,84€~~ 190,27€ 20% OFF + 5% CARD

 Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. Evolutionary Optimization in Dynamic Environments is the first comprehensive work on the application of EAs to dynamic optimization problems. It provides an extensive survey on research in the area and shows how EAs can be successfully used to <ul> <li> continuously and efficiently adapt a solution to a changing environment, </li> <li> find a good trade-off between solution quality and adaptation cost, </li> <li> find robust solutions whose quality is insensitive to changes in the environment, </li> <li> find flexible solutions which are not only good but that can be easily adapted when necessary. </li> </ul> All four aspects are treated in this book, providing a holistic view on the challenges and opportunities when applying EAs to dynamic optimization problems. The comprehensive and up-to-date coverage of the subject, together with details of latest original research, makes Evolutionary Optimization in Dynamic Environments an invaluable resource for researchers and professionals who are dealing with dynamic and stochastic optimization problems, and who are interested in applying local search heuristics, such as evolutionary algorithms.
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Anticipatory Learning Classifier Systems

by Martin V. Butz

~~118,59€~~ 94,87€ 20% OFF + 5% CARD

 Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning. Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system.
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Frontiers Of Evolutionary Computation

~~118,59€~~ 94,87€ 20% OFF + 5% CARD

 Brings together eleven contributions by international researchers, discussing significant issues in the field of Evolutionary Computation (EC). This work explores such topics as the role of building blocks, the balancing of exploration with exploitation, the modeling of EC algorithms, and more.
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Classical And Evolutionary Algorithms In The Optimization Of Optical Systems

by Darko Vasiljevic

101,38€ + 10% CARD

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Fall Out

by Sandra Glover

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 The music pulses, lights flash and raised voices echo in Hannah's head. Her parents are away and her impromptu house-party has got completely out-of-hand. But when Hannah wakes up the next morning with her head throbbing and the house wrecked, she realises these are the least of her problems.
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That'S Not Funny!

by Jeanne Willis; Illustration: Adrian Reynolds

7,71€

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 One day, just for a joke, Hyena puts a banana skin on Giraffe's path. When Giraffe slips and collides with a tree, a chain of unfortunate events begins which involves all the other animals. Hyena laughs and laughs at their misfortune. But the other animals have the last laugh when Hyena gets a fitting comeuppance and trips up on his own joke!
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Xbox 360 Forensics - A Digital Forensics Guide To Examining Artifacts

by Steven Bolt

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 Game consoles have evolved to become complex computer systems that may contain evidence to assist in a criminal investigation. From networking capabilities to chat, voicemail, streaming video and email, the game consoles are unrecognizable from complex computer systems. This title presents the information for the game console examiners.
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Cybercrime And Espionage - An Analysis Of Subversive Multi-Vector Threats

by John (Director, Security Solutions, Forsythe Technology And Co-Founder & Advisor, Bricata, Llc) Pirc

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 Provides the knowledge related to the realities seen in the execution of advanced attacks, their success from the perspective of exploitation and their presence within the industries. This book educates you on realities of advanced threats, which take form in a variety ways.
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Lectures On Rhetoric And Belles Lettres.

by Hugh Blair

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An Act For Erecting A Work-House In The

by Multiple Contributor

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An Abridgment Of The Publick Laws Of Vir

by Multiple Contributor

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The Trial Of Capt. John Porteous, Before

by John Porteous

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An Act For Punishing Mutiny And Desertio

by Multiple Contributor

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The Trial At Large Of Francis Henry De L

by Francis De La Motte

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William Harris, Alias Harries, Late Merc

by William Harries

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An Institute Of The Law Of Scotland. In

by John Erskine

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The Diary Maid; Or, Vocal Miscellany. Be

by Multiple Contributor

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