PHI Learning Pvt. Ltd.
|Number of Pages
There has been a movement over the years to make machines intelligent. With the advent of modern technology, AI has become the core part of day-to-day life. But it is accentuated to have a book that keeps abreast of all the state-of-the-art concepts (pertaining to AI) in simplified, explicit and elegant way, expounding on ample examples so that the beginners are able to comprehend the subject with ease.
The book on Artificial Intelligence, dexterously divided into 21 chapters, fully satisfies all these pressing needs. It is intended to put each and every concept related to intelligent system in front of the readers in the most simplified way so that while understanding the basic concepts, they will develop thought process that can contribute to the building of advanced intelligent systems.
Various cardinal landmarks pertaining to the subject such as problem solving, search techniques, intelligent agents, constraint satisfaction problems, knowledge representation, planning, machine learning, natural language processing, pattern recognition, game playing, hybrid and fuzzy systems, neural network-based learning and future work and trends in AI are now under the single umbrella of this book, thereby showing a nice blend of theoretical and practical aspects.
With all the latest information incorporated and several pedagogical attributes included, this textbook is an invaluable learning tool for the undergraduate and postgraduate students of computer science and engineering, and information technology.
• Highlights a clear and concise presentation through adequate study material
• Follows a systematic approach to explicate fundamentals as well as recent advances in the area
• Presents ample relevant problems in the form of multiple choice questions, concept review questions, critical thinking exercise and project work
• Incorporates various case studies for major topics as well as numerous industrial examples
About the Author
Prachi Joshi, PhD, is an Associate Professor, Department of Computer Engineering, MIT College of Engineering, Pune. Besides being involved in research activities, she has been teaching the graduate and postgraduate students also. She has also been co-guiding numerous projects in computer sciences at various engineering colleges. Her research areas include artificial intelligence and machine learning. She has a multiple research publications to her credit.|Parag Kulkarni, PhD, is CEO and Chief Scientist, EKLaT Research, Pune. Dr. Kulkarni is an entrepreneur, machine learning expert and innovation strategist. Through his consultations and innovative leadership, he has turned around fortune of more than one dozen start-ups in last two decades. He is pioneer of concepts systemic machine learning and systemic knowledge innovation. He is visiting researcher and faculty at various B-schools and technical schools of repute, including IITs, IIMs, Masaryk University, COEP, etc. Besides being the co-author of more than half a dozen books, he has also authored two books, namely, Knowledge Innovation Strategy and Reinforcement and Systemic Machine Learning for Decision Making as well as more than 220 research papers. Dr. Kulkarni is co-inventor of half a dozen patents as well. He has delivered more than 100 keynote addresses and numerous talks on machine learning, strategy and managing start-ups to deliver extraordinary impact on strategic perspective of thousands of researchers and professionals. He has worked very closely with Grassroots innovators and contributed to Grassroots innovations through his refreshing novel ideas in the fields of artificial intelligence and machine learning. His areas of interests include artificial intelligence, machine learning, business and knowledge innovation and data mining.
Table of Contents:
Preface • Acknowledgements
1. Introduction to Artificial Intelligence
2. Problem Solving
3. Uninformed Search
4. Informed Search
5. Intelligent Agent
6. Constraint Satisfaction Problems
7. Knowledge and Reasoning
8. Uncertain Knowledge and Reasoning
11. Expert Systems
12. Natural Language Processing
13. Decision Theory
14. Pattern Recognition
15. Game Playing
16. Perception and Action
17. Neural Network-based Learning
18. Fuzzy and Hybrid Intelligent Systems
19. Applications of Artificial Intelligence
20. Advance Topics in Artificial Intelligence
21. Concluding Remarks: AI-Present and Future