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Evolutionary Computation in Dynamic and Uncertain Environments
This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering systems is inevitable. Representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums, are presented. "Evolutionary Computation in Dynamic and Uncertain Environments" is a valuable reference for scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, natural computing and evolutionary computation.
Evolutionary Computation in Data Mining
This carefully edited book reflects and advances the state of the art in the area of Data Mining and Knowledge Discovery with Evolutionary Algorithms. It emphasizes the utility of different evolutionary computing tools to various facets of knowledge discovery from databases, ranging from theoretical analysis to real-life applications. "Evolutionary Computation in Data Mining" provides a balanced mixture of theory, algorithms and applications in a cohesive manner, and demonstrates how the different tools of evolutionary computation can be used for solving real-life problems in data mining and bioinformatics.
Evolutionary Computation for Modeling and Optimization
Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered.
Engineering Evolutionary Intelligent Systems
This edited volume 'Engineering Evolutionary Intelligent Systems' deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business or commerce.
Embedded Robotics : Mobile Robot Design and Applications with Embedded Systems
The EyeBot controller and mobile robots have evolved over more than a decade. This book gives an in-depth introduction to embedded systems and autonomous mobile robots, using the EyeBot controller (EyeCon) and the EyeBot mobile robot family as application examples. This book combines teaching and research material and can be used for courses in Embedded Systems as well as in Robotics and Automation.
Design by Evolution : Advances in Evolutionary Design
This book showcases the state of the art in evolutionary algorithms for design. The chapters are organized by experts in the following fields: evolutionary design and "intelligent design" in biology, art, computational embryogeny, and engineering.
Computer vision systems ; 6th International conference, ICVS 2008 Santorini, Greece, May 12-15, 2008 Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Computer Vision Systems, ICVS 2008, held in Santorini, Greece, May 12-15, 2008.
Computational intelligence in economics and finance ; Vol. II
Computational intelligence (CI), as an alternative to statistical and econometric approaches, has been applied to a wide range of economics and finance problems in recent years, for example to price forecasting and market efficiency. This book contains research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.
Computational intelligence and security ; Vol. 3801 ; International Conference, CIS 2005, Xi'an, China, December 15-19, 2005, Proceedings, Part I
The two volume set LNAI 3801 and LNAI 3802 constitute the refereed proceedings of the annual International Conference on Computational Intelligence and Security, CIS 2005, held in Xi'an, China, in December 2005. The 338 revised papers presented - 254 regular and 84 extended papers - were carefully reviewed and selected from over 1800 submissions. The first volume is organized in topical sections on learning and fuzzy systems, evolutionary computation, intelligent agents and systems, intelligent information retrieval, support vector machines, swarm intelligence, data mining, pattern recognition, and applications.
Computational intelligence : Methods and techniques
This book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. Those techniques are today commonly applied issues of artificial intelligence, e.g. to process speech and natural language, build expert systems and robots.
Computational Discovery of Scientific Knowledge : Introduction, Techniques, and Applications in Environmental and Life Sciences
Advances in technology have enabled the collection of data from scientific observations, simulations, and experiments at an ever-increasing pace. For the scientist and engineer to benefit from these enhanced data collecting capabilities, it is becoming clear that semi-automated data analysis techniques must be applied to find the useful information in the data. Computational scientific discovery methods can be used to this end: they focus on applying computational methods to automate scientific activities, such as finding laws from observational data. In contrast to mining scientific data, which focuses on building highly predictive models, computational scientific discovery puts a strong emphasis on discovering knowledge represented in formalisms used by scientists and engineers, such as numeric equations and reaction pathways. This state-of-the-art survey provides an introduction to computational approaches to the discovery of scientific knowledge and gives an overview of recent advances in this area, including techniques and applications in environmental and life sciences.
Machine Learning: ECML 2007 ; 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings
The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the ?rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was?rstheldin1997inTrondheim, Norway.
Linear Genetic Programming
Linear Genetic Programming examines the evolution of imperative computer programs written as linear sequences of instructions. In contrast to functional expressions or syntax trees used in traditional Genetic Programming (GP), Linear Genetic Programming (LGP) employs a linear program structure as genetic material whose primary characteristics are exploited to achieve acceleration of both execution time and evolutionary progress.
Bioinspired optimization methods and their applications ; 9th International conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Bioinspired Optimization Methods and Their Applications, BIOMA 2020, held in Brussels, Belgium, in November 2020. The 24 full papers presented in this book were carefully reviewed and selected from 68 submissions. The papers in this BIOMA proceedings specialized in bioinspired algorithms as a means for solving the optimization problems and came in two categories: theoretical studies and methodology advancements on the one hand, and algorithm adjustments and their applications on the other.
Autonomic communication ; Vol. 3854 : 2nd International IFIP Workshop, WAC 2005, Athens, Greece, October 2-5, 2005, Revised Selected Papers
The Second IFIP Workshop on Autonomic Communication (WAC 2005) took place on October 2–5, 2005, IFIP TC6 provided scientific sponsorship through Working Groups IFIP WG6. 6 (Management of Networks and Distributed Systems) and IFIP WG6. 3 (Performance of Communication Systems). The workshop was organized at a time when the – yet to be well defined – field of autonomic communication (AC) is attracting the interest of both the scientific community and the research funding organizations. The latter is manifested, on one hand, by the numerous recent relevant research exploratory forums, workshop panels, preliminary forward-looking position papers, research outlooks and frameworks and, on the other hand, by the commitment of the FET program of the European Commission in Europe to funding long-term research in this area for the next four years.
Automatic Quantum Computer Programming : A Genetic Programming Approach
Computer science will be radically transformed if ongoing efforts to build large-scale quantum computers eventually succeed and if the properties of these computers meet optimistic expectations. Nevertheless, computer scientists still lack a thorough understanding of the power of quantum computing, and it is not always clear how best to utilize the power that it is understood. This dilemma exists because quantum algorithms are difficult to grasp and even more difficult to write. Despite large-scale international efforts, only a few important quantum algorithms are documented, leaving many essential questions about the potential of quantum algorithms unanswered.
Automated technology for verification and analysis ; 6th International Symposium, ATVA 2008, Seoul, Korea, October 20-23, 2008. Proceedings
This book constitutes the refereed proceedings of the 6th International Symposium on Automated Technology for Verification and Analysis, ATVA 2008, held in Seoul, Korea, in October 2008.
Artificial neural networks – ICANN 2007 ; 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part I
This book contains learning theory, advances in neural network learning methods, ensemble learning, spiking neural networks, advances in neural network architectures neural network technologies, neural dynamics and complex systems, data analysis, estimation, spatial and spatio-temporal learning, evolutionary computing, meta learning, agents learning, complex-valued neural networks, as well as temporal synchronization and nonlinear dynamics in neural networks.
Artificial immune systems ; Vol. 3627 ; 4th International conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings
Your immune system is unique. It is in many ways as complex as your brain, butit is not centred in one location, like the brain. It is not a single organ—it consistsof many different cell types, diverse methods of intercellular communication, andmany different organs. Its functionality is blurred throughout you—we can’textract the immune system, or point to where it begins and ends. The immunesystem is not separable from the system it protects. It has integral links to everyorgan of our bodies.This has radical implications for the field of Artificial Immune Systems (AIS),that we are only now beginning to comprehend. One of the first insights is thatmodelling the immune system, or developing any kind of immune algorithm, isdifficult. The immune system is one aspect of biology that we find difficult toapply simple reductionist explanations to. We can very successfully extract sub-processes of the whole and create immune algorithms based on those processes.
Artificial evolution ; 8th International Conference, Evolution artificielle, EA 2007, Tours, France, October 29-31, 2007, revised selected papers
This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Artificial Evolution, EA 2007, held in Tours, France in October 2007.
