Description
Book SynopsisFundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.
Trade Review“The book is a good textbook for C S courses, as well as a helpful resource for people working in academia or industry. It will be beneficial in teaching the fundamental concepts of AI. … Along these lines, for people interested in learning the theory of AI, it is both a good textbook and valuable resource.” (Gulustan Dogan, Computing Reviews, December 30, 2020)
“It is very astonishing that hardly any curricula come back to Norbert Wiener’s cybernetics. His theory of systems will be the safe background for any new system to be developed. I wish the author still much success in this field, you can contribute a lot to the welfare of the human society.” (Christian Posthoff, zbMATH 1442.68001, 2020)
Table of ContentsIntroduction.- Logic and Inferencing.- First Order Predicate Logic.- Rule Based Reasoning.- Introduction to Prolog Language.- Knowledge Representation and Reasoning.- Networks Based Representation.- State Space Search.- Heuristic Search.- Constraint Satisfaction Problems.- Search and Game Playing.- Reasoning in Uncertain Environments.- Planning.- Natural Language Processing.- Machine Learning.- Machine Vision.- Bibliography.
