AI has two main goals — building intelligent machines and understanding the nature of intelligence. Expert systems are computer-based systems that use knowledge often acquired from human experts to solve problems reading such expertise as in medical diagnosis, legal advising, tax planning, image interpretation and engineering design. AI and ES are linked via Knowledge Engineering (KE). KE is concerned with reducing a large body of knowledge to a set of facts and rules of a knowledge base and the inference procedures required for utilizing that knowledge for problem solving. KE is concerned with the task of building expert systems using appropriate tools.
The main features of the book are as follows:
1. LUCID and Simple Language
2. Large number of solved examples
3. CASE STUDIES, experiments of AI in LISP and PROLOG programming of all Indian Universities.
|Table of Contents:|
1. AI INTRODUCTION
2. AI APPROACHES
3. GAMES SOLVING (ADVERBIAL SEARCH)
4. KNOWLEDGE REPRESENTATION
5. REASONING UNCERTAINTY
6. NATURAL LANGUAGE PROCESSING
8. EXPERT SYSTEMS
9. I PROGRAMMING LANGUAGES—LISP AND PROLOG
10. TESTING AI PROGRAMS