I. K. International Pvt Ltd, 2008 M09 20 - 480 pages
Artificial Intelligence (AI) is an emerging discipline of computer science. It deals with the concepts and methodologies required by computer to perform an intelligent activity. The spectrum of computer science is very wide and it enables the computer to handle almost every activity, which human beings can. It deals with defining the basic problem from viewpoint of solving it through computer, finding out the total possibilities of solution, representing the problem from computational orientation, selecting data structures, finding the solution through searching the goal in search space dealing with the real world uncertain situations, etc. It also develops the techniques for learning and understanding, which make the computer able to exhibit an intelligent behavior. The list is exhaustive and is applied nowadays in almost every field of technology.
This book presents almost all the components of AI like problem solving, search techniques, knowledge concepts, expert system and many more in a very simple language. One of the unique features of this book is inclusion of number of solved examples; in between the chapters and also at the end of many chapters. Real life examples have been discussed to make the reader conversant with the intricate phenomenon of computer science in general, and artificial intelligence in particular. The book is primarily developed for undergraduate and postgraduate engineering students.
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PROBLEM SOLVING THROUGH AI 2861
HEURISTIC SEARCH 62105
INTRODUCTION TO KNOWLEDGE 106125
ADVANCED KNOWLEDGE REPRESENTATION
PROGRAMMING 196239 LANGUAGES
Adwet algorithm analysis applications arguments Artificial Intelligence basic Bayes theorem belief called chess clauses concept conceptual dependency conceptual graph considered constraints defined DENDRAL depth-first search described developed digit discussed domain evaluation evidence example expert system expression facts formal given goal grammar graph Hence heuristic function human experts hypothesis inference input integer interpretation knowledge acquisition knowledge base knowledge engineering knowledge representation learning LISP logic machine match means method move MYCIN natural language processing neural network neuron node noun object operator output parsing path pattern perform possible predicate calculus predicate logic probability problem solving procedure production rules PROLOG proposition propositional calculus rain real world reasoning represented search techniques semantic sentence sequence shown in Fig situation solution stored string structure symbol symptoms syntactic task theorem theory tree understanding variable various verb