ABSTRACT

With all the material available in the field of artificial intelligence (AI) and soft computing-texts, monographs, and journal articles-there remains a serious gap in the literature. Until now, there has been no comprehensive resource accessible to a broad audience yet containing a depth and breadth of information that enables the reader to fully understand and readily apply AI and soft computing concepts.
Artificial Intelligence and Soft Computing fills this gap. It presents both the traditional and the modern aspects of AI and soft computing in a clear, insightful, and highly comprehensive style. It provides an in-depth analysis of mathematical models and algorithms and demonstrates their applications in real world problems.
Beginning with the behavioral perspective of "human cognition," the text covers the tools and techniques required for its intelligent realization on machines. The author addresses the classical aspects-search, symbolic logic, planning, and machine learning-in detail and includes the latest research in these areas. He introduces the modern aspects of soft computing from first principles and discusses them in a manner that enables a beginner to grasp the subject. He also covers a number of other leading aspects of AI research, including nonmonotonic and spatio-temporal reasoning, knowledge acquisition, and much more.
Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain is unique for its diverse content, clear presentation, and overall completeness. It provides a practical, detailed introduction that will prove valuable to computer science practitioners and students as well as to researchers migrating to the subject from other disciplines.

chapter 2|33 pages

The Psychological Perspective of Cognition

chapter 3|24 pages

Production Systems

chapter 4|41 pages

Problem Solving by Intelligent Search

chapter 5|33 pages

The Logic of Propositions and Predicates

chapter 6|22 pages

Principles in Logic Programming

chapter 7|23 pages

Default and N on-Monotonic Reasoning

chapter 9|40 pages

Dealing with Imprecision and Uncertainty

chapter 10|45 pages

Structured Approach to Fuzzy Reasoning

chapter 11|28 pages

Reasoning with Space and Time

chapter 12|25 pages

Intelligent Planning

chapter 13|32 pages

Machine Learning Techniques

chapter 14|34 pages

Machine Learning Using Neural Nets

chapter 15|27 pages

Genetic Algorithms

chapter 16|19 pages

Realizing Cognition Using Fuzzy Neural Nets

chapter 17|37 pages

Visual Perception

chapter 18|24 pages

Linguistic Perception

chapter 19|26 pages

Problem Solving by Constraint Satisfaction

chapter 20|20 pages

Acquisition of Knowledge

chapter 23|41 pages

Case Study I:

Building a System for Criminal Investigation

chapter 25|2 pages

The Expectations from the Readers