Artifical intelligence has grown rapidly as a field of research and industrial application in recent years. Whereas traditionally, AI used techniques drawn from rule-based and logic programming systems, interest is now growing in less precise heuristic methods, notably genetic algorithms, fuzzy logic, and neural networks. This textbook provides a first course in AI which covers these new technologies and how they may be applied. Prerequisites are minimal: a basic understanding of computer science and mathematics are sufficient and so this will be suitable for undergraduates coming to this subject for the first time. Professor Munakata is a leading figure in this field and has given courses on this topic extensively. As a result, students and researchers will enjoy this authoritative introduction to the subject. In each topic the book covers the most essential and widely employed material, particularly as it is used in real-world applications. Its emphasis is on concise yet clear descriptions of the technical substance.The schema theorem tells us which and how parts of the solutions are likely to survive and grow as iterations proceed. In effect, the genetic algorithm ... be manually placed together to form good solutions. The concept is a widely ... Programming. Genetic programming is a subfield of genetic algorithms, where each solutionanbsp;...
|Title||:||Fundamentals of the New Artificial Intelligence|
|Publisher||:||Springer Science & Business Media - 1998-01|