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English | 2022 | ISBN: 1683922239 | 739 pages | True PDF | 69.35 MB
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
+ 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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