Information Processing with Evolutionary Algorithms
Subtitle: From Industrial Applications to Academic Speculations (Advanced Information and Knowledge Processing)
Contributors: Manuel Grana (Editor); Richard Duro (Editor); Alicia d'Anjou (Editor); Paul P. Wang (Editor)
Edition: 1 edition
Publisher: Springer
Published: November 19, 2004
Language: eng
Format: Hardcover
Number of pages: 334
ISBN-13: 9781852338664
Subjects: Artificial intelligence; Expert Systems; Computers; Artificial Intelligence - General; Information Storage & Retrieval; Computers - General Information; Evolutionary programming (Computer science); Computer Books: General; Evolutionary programming (Comp; Computer Science; Computers / Computer Science; Genetic algorithms; Electronic data processing
First sentence: Over the past 50 years, computer science has seen quite a number of fundamental inventions and, coming along with them, revolutions concerning the way how software systems are able to deal with data.
Description: The last decade of the 20th century has witnessed a surge of interest in num- ical, computation-intensive approaches to information processing. The lines that draw the boundaries among statistics, optimization, arti cial intelligence and information processing are disappearing, and it is not uncommon to nd well-founded and sophisticated mathematical approaches in application - mains traditionally associated with ad-hoc programming. Heuristics has - come a branch of optimization and statistics. Clustering is applied to analyze soft data and to provide fast indexing in the World Wide Web. Non-trivial matrix algebra is at the heart of the last advances in computer vision. The breakthrough impulse was, apparently, due to the rise of the interest in arti cial neural networks, after its rediscovery in the late 1980s. Disguised as ANN, numerical and statistical methods made an appearance in the - formation processing scene, and others followed. A key component in many intelligent computational processing is the search for an optimal value of some function. Sometimes, this function is not evident and it must be made explicit in order to formulate the problem as an optimization problem. The search - ten takes place in high-dimensional spaces that can be either discrete, or c- tinuous or mixed. The shape of the high-dimensional surface that corresponds to the optimized function is usually very complex. Evolutionary algorithms are increasingly being applied to information processing applications that require any kind of optimization.