Essentials Of A I And Soft Computing

ESSENTIALS OF AI AND SOFT COMPUTING

The book has been primarily designed for the beginners in the subject. It has been written from the students' perspective, making it easy to understand. The contents are briefly explained with the help of examples in a direct and a pragmatic approach. Each chapter begins with the basics and is standalone; the dependence of the chapters on previous concepts has been minimized. The text is aimed to balance the mix of notation and words in mathematical statements. Artificial Intelligence and Soft Computing topics are often expressed in terms of algorithms, hence key algorithms are introduced with their explanations. These algorithms are expressed in words and in an easy to understand form of structured psuedocodes. The students should easily grasp the psuedocodes used in the text to express the algorithms, regardless of whether they have formally studied programming languages. KEY FEATURES • Short and concise explanation with examples. • Direct and pragmatic writing style. • Structured psuedocodes for explaining algorithms. • Balanced mix of notation and words in mathematical statements. • Meticulously organised chapter for effective teaching and learning. • Chapter-end Exercises to help students practice and assess their knowledge. TARGET AUDIENCE • BCA and MCA • B.Sc. Computer Science and Information Technology • B.Tech. Computer Science Engineering and Information Technology

ESSENTIALS OF A.I AND SOFT COMPUTING.

Fundamentals of the New Artificial Intelligence

The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Our goal is not to cover every latest progress in the fields, nor to discuss every detail of various techniques that have been developed. New sections/subsections added in this edition are: Simulated Annealing (Section 3.7), Boltzmann Machines (Section 3.8) and Extended Fuzzy if-then Rules Tables (Sub-section 5.5.3). Also, numerous changes and typographical corrections have been made throughout the manuscript. The Preface to the first edition follows. General scope of the book Artificial intelligence (AI) as a field has undergone rapid growth in diversification and practicality. For the past few decades, the repertoire of AI techniques has evolved and expanded. Scores of newer fields have been added to the traditional symbolic AI. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing. The newer fields include neural networks, genetic algorithms or evolutionary computing, fuzzy systems, rough set theory, and chaotic systems.