Introduction To Artificial Intelligence

By AKERKAR, RAJENDRA more
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Product Specifications

Publisher PHI Learning
ISBN 9788120349971
Author: AKERKAR, RAJENDRA
Number of Pages 440
Edition Second Edition
Available
Available in all digital devices
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About The Book Introduction To Artificial Intelligence
Book Summary:

This comprehensive text acquaints the readers with the important aspects of artificial intelligence (AI) and intelligent systems and guides them towards a better understanding of the subject.

The text begins with a brief introduction to artificial intelligence, including application areas, its history and future, and programming. It then deals with symbolic logic, knowledge acquisition, representation and reasoning. The text also lucidly explains AI technologies such as computer vision, natural language processing, pattern recognition and speech recognition. Topics such as expert systems, neural networks, constraint programming and case-based reasoning are also discussed in the book.

In the Second Edition, the contents and presentation have been improved thoroughly and in addition six new chapters providing a simulating and inspiring synthesis of new artificial intelligence and an appendix on AI tools have been introduced.

The treatment throughout the book is primarily tailored to the curriculum needs of B.E./B.Tech. students in Computer Science and Engineering, B.Sc. (Hons.) and M.Sc. students in Computer Science, and MCA students. The book is also useful for computer professionals interested in exploring the field of artificial intelligence.


Key Features

Exposes the readers to real-world applications of AI.
Concepts are duly supported by examples and cases.
Provides appendices on PROLOG, LISP and AI Tools.
Incorporates most recommendations of the Curriculum Committee on Computer Science/Engineering for AI and Intelligent Systems.
Exercises provided will help readers apply what they have learned.


Table of Contents:

Preamble


1. Overview of Artificial Intelligence

2. Symbolic Logic

3. Knowledge Acquisition and Representation

4. Reasoning and KRR Systems

5. Uncertainty

6. Search Techniques

7. AI Technologies

8. Expert Systems

9. Neural Networks

10. Case-Based Reasoning

11. Constraint Programming

12. Intelligent Agents

13. Planning

14. Soft Computing

15. Robotics

16. Machine Learning

17. Intelligent Systems

18. Applications of Artificial Intelligence


Appendices

A: Projects

B: PROLOG

C: LISP

D: AI Tools

Glossary

Bibliography

Index

 

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