الصفحة 1
الصفحة 1
Theory of Evolutionary Computation : Recent Developments in Discrete Optimization
Reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three chapters on how to measure the complexity of a search heuristic: black-box complexity, a counterpart of classical complexity theory in black-box optimization; parameterized complexity, aimed at a more fine-grained view of the difficulty of problems; and the fixed-budget perspective, which answers the question of how good a solution will be after investing a certain computational budget. The book then describes theoretical results on three important questions in evolutionary computation: how to profit from changing the parameters during the run of an algorithm; how evolutionary algorithms cope with dynamically changing or stochastic environments; and how population diversity influences performance. Finally, the book looks at three algorithm classes that have only recently become the focus of theoretical work: estimation-of-distribution algorithms; artificial immune systems; and genetic programming.
Stochastic Algorithms: Foundations and Applications ; 4th International Symposium, SAGA 2007, Zurich, Switzerland, September 13-14, 2007, Proceedings
Constitutes the refereed proceedings of the 4th International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2007, held in Zurich, Switzerland, in September 2007. The 9 revised full papers and 5 invoted papers presented were carefully reviewed and selected out of 31 submissions for inclusion in the book. The contributed papers included in this volume cover both theoretical as well as applied aspects of stochastic computations whith a special focus on investigating the power of randomization in algorithmics
Stochastic Algorithms : Foundations and Applications; 3rd International Symposium, SAGA 2005, Moscow, Russia, October 20-22, 2005
Constitutes the refereed proceedings of the Third International Symposium on Stochastic Algorithms: Foundations and Applications, SAGA 2005, held in Moscow, Russia in October 2005. This title includes papers that cover both theoretical as well as applied aspects of stochastic computations with a special focus on the algorithmic ideas.
Spatially structured evolutionary algorithms : Artificial evolution in space and time
Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks.
Soft Computing for Knowledge Discovery and Data Mining
The first three parts of this book are devoted to the principal constituents of soft computing: neural networks, evolutionary algorithms and fuzzy logic. The last part compiles the recent advances in soft computing for data mining, such as swarm intelligence, diffusion process and agent technology. This book provides investigators in the fields of information systems, engineering, computer science, operations research, bio-informatics, statistics and management with a profound source for the role of soft computing in data mining.
Soft Computing for Hybrid Intelligent Systems
Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, This edited book comprises papers on diverse aspects of soft computing and hybrid intelligent systems. There are theoretical aspects as well as application papers. The first part consists of papers with the main theme of intelligent control, The second part contains papers with the main theme of pattern recognition, The third part contains papers with the themes of intelligent agents and social systems, The fourth part contains papers that deal with the hardware implementation of intelligent systems for solving particular problems. The fifth part contains papers that deal with modeling, simulation and optimization for real-world applications.
Soft Computing : Methodologies and Applications
This carefully edited book covers a wide range of application areas of soft computing like optimization, data analysis and data mining, fault diagnosis, control as well as traffic and transportation systems. It contains 25 revised contributions from the 8th Online World Conferences on Soft Computing (WSC8). The collected papers show how the major soft computing techniques, fuzzy systems, neural networks and evolutionary algorithms and especially hybrid systems combining methods from these fields, lead to successful industrial applications. The reader will find an interesting, inspiring and wide variety of soft computing techniques and applications in this book.
Signal Processing Techniques for Knowledge Extraction and Information Fusion
This state-of-the-art resource brings together the latest findings from the cross-fertilization of signal processing, machine learning and computer science. The emphasis is on demonstrating synergy of different signal processing methods with knowledge extraction and heterogeneous information fusion. Issues related to the processing of signals with low signal-to-noise ratio, solving real-world multi-channel problems, and using adaptive techniques where nonstationarity, uncertainty and complexity play major roles are addressed. Particular methods include Independent Component Analysis, Support Vector Machines, Distributed and Collaborative Adaptive Filtering, Empirical Mode Decomposition, Self Organizing Maps, Fuzzy Logic, Evolutionary Algorithms and several others used frequently in these fields. Also included are both important and novel applications from telecommunications, renewable energy and biomedical engineering.
Scalable Optimization via Probabilistic Modeling : From Algorithms to Applications
The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited.
Representations for Genetic and Evolutionary Algorithms
The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently.
Progress in artificial intelligence ; 20th EPIA Conference on Artificial Intelligence, EPIA 2021, Virtual Event, September 7–9, 2021, Proceedings
This book constitutes the refereed proceedings of the 20th EPIA Conference on Artificial Intelligence, EPIA 2021, held virtually in September 2021. The 62 full papers and 6 short papers presented were carefully reviewed and selected from a total of 108 submissions. The papers are organized in the following topical sections: artificial intelligence and IoT in agriculture; artificial intelligence and law; artificial intelligence in medicine; artificial intelligence in power and energy systems; artificial intelligence in transportation systems; artificial life and evolutionary algorithms; ambient intelligence and affective environments; general AI; intelligent robotics; knowledge discovery and business intelligence; multi-agent systems: theory and applications; and text mining and applications.
Pricing Portfolio Credit Derivatives by Means of Evolutionary Algorithms
Svenja Hager aims at pricing non-standard illiquid portfolio credit derivatives which are related to standard CDO tranches with the same underlying portfolio of obligors. Instead of assuming a homogeneous dependence structure between the default times of different obligors, as it is assumed in the standard market model, the author focuses on the use of heterogeneous correlation structures. The intention is to find a correlation matrix sufficiently flexible so that all tranche spreads of a CDO structure can be reproduced simultaneously. This allows for consistent pricing. The calibrated model can then be used to determine the price of non-standard contracts. As there is no standard optimization technique to derive the correlation structure from market prices, Evolutionary Algorithms are applied.
Practice and Theory of Automated Timetabling VI ; 6th International Conference, PATAT 2006 Brno, Czech Republic, August 30-September 1, 2006 Revised Selected Papers
This volume contains a selection of the papers presented at the Sixth Int- national Conference on the Practice and Theory of Automated Timetabling (PATAT) which was organized in Brno, Czech Republic, from August 30 to September 1 of 2006. The PATAT conferences, which are held every 2 years, bring together - searchers and practitioners from across the broad spectrum of inter-disciplinary research activity in search methodologies for automated timetable generation.
Practice and Theory of Automated Timetabling V ; 5th International Conference, PATAT 2004, Pittsburgh, PA, USA, August 18-20, 2004, Revised Selected Papers
This volume contains a selection of the papers presented at the Sixth Int- national Conference on the Practice and Theory of Automated Timetabling (PATAT) which was organized in Brno, Czech Republic, from August 30 to September 1 of 2006. The PATAT conferences, which are held every 2 years, bring together - searchers and practitioners from across the broad spectrum of inter-disciplinary research activity in search methodologies for automated timetable generation. This includes university timetabling, school timetabling, personnel rostering, transportation timetabling, sports scheduling. The programme of the 2006 c- ference featured 70 presentations which represented the state of the art in au- mated timetabling: there were four plenary papers, 17 full papers, 41 extended abstracts, and eight system demonstrations. After the conference, all authors were invited to submit their papers to a second round of rigorous refereeing for this volume of selected revised papers. We are pleased to have accepted 25 - pers for this volume. This ?gure represents the highest number of acceptances in a PATAT post-proceedings volume and is a testament to the high standards of the papers that were submitted. The organization of the book is structured around particular problem areas.
Parameter Setting in Evolutionary Algorithms
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 and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.
Parallel problem solving from nature – PPSN XVI ; 16th International conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II
Constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, held in Leiden, The Netherlands, in September 2020. The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration; Bayesian- and surrogate-assisted optimization; benchmarking and performance measures; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world applications; reinforcement learning; and theoretical aspects of nature-inspired optimization.
Parallel Problem Solving from Nature – PPSN XVI ; 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I
Constitutes the refereed proceedings of the 16th International Conference on Parallel Problem Solving from Nature, PPSN 2020, held in Leiden, The Netherlands, in September 2020. The 99 revised full papers were carefully reviewed and selected from 268 submissions. The topics cover classical subjects such as automated algorithm selection and configuration ; Bayesian- and surrogate-assisted optimization ; benchmarking and performance measures ; combinatorial optimization; connection between nature-inspired optimization and artificial intelligence ; genetic and evolutionary algorithms ; genetic programming; landscape analysis ; multiobjective optimization ; real-world applications ; reinforcement learning ; and theoretical aspects of nature-inspired optimization.
Optimisation in Computational Fluid Dynamics
The numerical optimization of practical applications is an issue of growing importance in research and industry. It allows both the exploration of non-trivial configurations differing widely from all known solutions and the step-by-step improvement of existing designs.The purpose of this book is to introduce the state of the art concerning this issue, referred to in the book as CFD-based Optimization (CFD-O). Many complementary applications are presented, so that interested researchers and engineers will get a clear view of the present possibilities for all problems where the numerical optimization process relies on evaluations obtained through Computational Fluid Dynamics.
Neural Networks in a Softcomputing Framework
This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model.
Nature Inspired Problem-Solving Methods in Knowledge Engineering ; 2nd International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part II
The second of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007.
