English | 2022 | ISBN: 1683922239 | 739 pages | True PDF | 69.35 MB
This third edition provides a comprehensive, colorful, up-to-date, and accessible presentation of AI without sacrificing theoretical foundations. It includes numerous examples, applications, full color images, and human- interest boxes to enhance student interest. New chapters on deep learning, AI security, and AI programming are included. Advanced topics cover neural nets, genetic algorithms, natural language processing, planning, and complex board games. Companion files provide appendices, resources, applications, selected solutions, and figures from the book(available with Amazon proof of purchase by writing to the publisher at info@merclearning.com). Numerous instructors’ resources are available upon adoption.
Features
+Includes new chapters on deep learning, AI security, and AI programming
+Provides a comprehensive, colorful, up to date, and accessible presentation of AI without sacrificing theoretical foundations
+ Uses numerous examples, applications, full color images, and human interest boxes to enhance student interest
+ Introduces important AI concepts e.g., robotics, use in video games, neural nets, machine learning, and more thorough practical applications
+Features over 300 figures and color images with worked problems detailing AI methods and solutions to selected exercises
+Includes companion files with resources, simulations, selected solutions, and figures from the book(available with Amazon proof of purchase by writing to the publisher at info@merclearning.com).
+ Provides numerous instructors’ resources, including: solutions to exercises, Microsoft PP slides, etc.
Table of Contents
1: Overview of AI. 2: Uninformed Search. 3: Intelligent Search Methods. 4: Search Using Games I. 5: Logic in AI. 6: Knowledge Representation. 7: Production Systems. 8. Uncertainty in AI. 9: Expert Systems. 10: Machine Learning and Neural Networks. 11: Deep Learning 12: Search Inspired by Mother Nature. 13: Natural Language Processing.14: Automated Planning. 15: Robotics. 16. Advanced Computer Games. 17. Reprise. 18. AI and Security. 19. AI Programming. Appendices.
About the Authors
Stephen Lucci holds a Ph.D. from the CUNY Graduate School and currently teaches computer science at The City College of New York. Dr. Lucci has published in the areas of high-performance computing and artificial intelligence. Sarhan M. Musa, PhD teaches numerous courses at Prairie View A&M and is the author of several books including Computational Nanophotonics (CRC Press) and Finite Element Analysis (MLI). Danny Kopec (Late) taught at Brooklyn College. He authored several books and journal articles and was an International Chess Master.
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