<p>Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. Th
Soft Computing and Intelligent Systems Design: Theory, Tools and Applications
β Scribed by Fakhreddine O. Karray, Clarence W De Silva
- Publisher
- Addison Wesley
- Year
- 2004
- Tongue
- English
- Leaves
- 585
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Traditional artificial intelligence (AI) techniques are based around mathematical techniques of symbolic logic, with programming in languages such as Prolog and LISP invented in the 1960s. These are referred to as "crisp" techniques by the soft computing community. The new wave of AI methods seeks inspiration from the world of biology, and is being used to create numerous real-world intelligent systems with the aid of soft computing tools. These new methods are being increasingly taught at the upper end of the curriculum, sometimes as an adjunct to traditional AI courses, and sometimes as a replacement for them. Where a more radical approach is taken and the course is being taught at an introductory level, we have recently published Negnevitsky's book. Karray and Silva will be suitable for the majority of courses which will be found at an advanced level.Β Karray and de Silva cover the problem of control and intelligent systems design using soft-computing techniques in an integrated manner.Β They present both theory and applications, including industrial applications, and the book contains numerous worked examples, problems and case studies. Covering the state-of-the-art in soft-computing techniques,Β the book givesΒ the reader sufficient knowledge to tackle a wide range of complex systems for which traditional techniques are inadequate.Β
π SIMILAR VOLUMES
<p>Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. Th
<p>Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. Th
<span>Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control.
<p>This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing and cryptanalysis. It gathers high-quality papers presented at the International Conference on