• Title: Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp
• Author(s) Peter Norvig
• Publisher: Morgan Kaufmann; 1 edition; eBook (MIT Licensed, 2018)
• License(s): MIT License
• Paperback: 946 pages
• eBook: PDF
• Language: English
• ISBN-10: 1558601910
• ISBN-13: 978-1558601918
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Book Description

This book is an overview of classical artificial intelligence (AI) programming via actual implementation of landmark systems (case studies). For the student interested in AI, Paradigms of Artificial Intelligence Programming is an invaluable history lesson. Even the programmer who is relatively uninterested in AI will find value in the book's basic introduction to Lisp and case studies written in Lisp.

This is the first text to teach advanced Common Lisp techniques in the context of building major AI systems.

By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts.

It teaches advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts.

The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions.

This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

• Peter Norvig is an American computer scientist. He is a director of research at Google Inc., and used to be its director of search quality.

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• Artificial Intelligence and Logic Programming
• LISP and Common LISP Programming
• Machine Learning
• Neural Networks and Deep Learning
• Algorithms and Data Structures

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