Artificial Intelligence Simplified

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The book introduces key Artificial Intelligence (AI) concepts in an easy-to-read format with examples and illustrations. A complex, long, overly mathematical textbook does not always serve the purpose of conveying the basic AI concepts to most people. Someone with basic knowledge in Computer Science can have a quick overview of AI (heuristic searches, genetic algorithms, expert systems, game trees, fuzzy expert systems, natural language processing, super intelligence, etc.) with everyday examples. Published by: CSTrends LLP. ISBN-13: 978-1-944708-00-9 ISBN: 1-944708-00-6 (paperback)

  1. Author Information
  2. AI Resources
  3. FAQ
  4. Information for Libraries and Institutions

Ordering Information

  1. Barnes & Noble
  2. (US)(International: Australia, Canada, France, Germany, India, Italy, Japan, Mexico, Spain, UK ). Note: in some locations, only e-books are available. Contact Amazon help desk, if you have questions.
  3. Ingram Distribution
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Information for Libraries and Institutions

  1. PCIP data (PDF, Word)
  2. OCLC Worldcat/Skyriver
  3. MARC records (mrc, txt)

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Binto George is a professor in School of Computer Sciences at Western Illinois University, Macomb, IL, USA. He joined WIU after working at Rutgers University, Newark, NJ. Dr George received his Ph.D. from Indian Institute of Science, Bangalore. Dr George has several publications in Computer Science and has been the principal investigator of National Science Foundation funded curriculum research. He loves teaching and developing new courses. He is committed to making Computer Science accessible to all. Dr. George is a member of the IEEE Computer Science Society and the Association for Computing Machinery.

Gail Carmichael is currently a software developer at Shopify, where she is about to embark on a new and exciting education project. She previously worked as a full-time instructor at Carleton University, where she taught both majors and non-majors a variety of computer science courses. She is particularly passionate about teaching beginners and enticing them to fall in love with computer science, whether as a major or as a tool to help them in their own fields. She co-founded Carleton University's Women in Science and Engineering, helped launch the now Ontario-wide Go Code Girl high school outreach program, and has developed and taught many computing workshops and courses for folks of all ages.


  1. Top 20 Artificial Intelligence Books & Whitepapers (Richtopia)
  2. Sciwri author interview.


Why another book on AI?

We felt that most books are unnecessarily complex and overly mathematical. This book simplifies AI concepts and present them in an easy to read format. Now that companies spend billions of dollars on AI, we feel that it is time for everyone to have some knowledge of AI.

What background should I need to read this book?

If you have some computer science background, you should be able to easily understand this book. If you don't know anything about computer science, there are many resources available online. You may also check some of our articles here.

I am a student - how is this book useful for my AI course?

It helps you understand basic AI concepts. Armed with that foundation, you should be able to better tackle advanced AI books or dive into specific topic areas such as Neural Networks, Expert Systems, NLP, Genetic Algorithms, Heuristic Searches. Understanding broader concepts before dwelling into specifics will be helpful for most people - especially if you are a whole-to-part learner.

I have a problem with my order. Who should I contact?

You should contact your retailer from where you bought the book regarding problems with your order. In rare occasions, there can be printing/production issues. So if the printing is bad, etc. contact the seller to obtain a replacement copy. If you have comments about the book or its contents, please contact us so that we can improve our future editions.

I am an instructor - How can I use this book in my classroom?

Your students can develop an overview of AI by reading this book. This way, students can better appreciate the more challenging components of your course. You can also find additional resources such as reference books, conference/journal papers, videos and other information to complete your course requirements. Or if you are using another textbook, you can suggest this book as supplemental reading. The book should work fine even for non-major courses on AI. If you are planning for a new non-major course on AI or considering a new book for an already existing course, you can choose this book.

I am an instructor - May I have an evaluation copy?

Please contact us at Thank you for helping us to keep costs down for students by choosing electronic evaluation copy, if that works for you. If you have adopted the book for your course, we can send you a courtesy desk copy.

The resources are organized chapter-wise. About external links: We cannot guarantee their contents. If you feel there is a problem, please let us know. We are still building this page - more resources will be added later. If you like to suggest a link, please email us.

Chapter 1: Introduction

  1. America Building Robot Army for the Future (DOC TV Video)
  2. 15 Most Advanced Robots Invented (Planet Dolan Video)
  3. A Ride in the Google Self Driving Car (Google Self-Driving Car Video)
  4. How Smart is Today's Artificial Intelligence (PBS Video)
  5. IBM World of Watson (IBM Watson Video)(You may skip to 00:06:00)
  6. Deep Blue Beats G. Kasparov (Eustake)

Chapter 2: Scheduling with Search Methods

  1. Introduction to Algorithms (MIT Open Course)
  2. Depth-First Search (MIT Open Course)
  3. Breadth-First Search (MIT Open Course)
  4. BFS/DFS Animations (Steven Skiena)
  5. A* path finding demo (Mr Koka)

Chapter 3: Accommodating Surprises with Planning Techniques

  1. AI Planning for Robots (Ai Austin)
  2. Artificial Intelligence Planning Examples (Kush Singh)

Chapter 4: Evolving Schedules with Genetic Algorithms

  1. What is Genetic Algorithm? (MATLAB)

Chapter 5: Learning from Experience With Neural Networks

  1. Introduction to Neural Network (Jesus Suarez)

Chapter 6: Expert Systems for Diagnosis

  1. Rule-based systems and Knowledge Engineering (Chao Xu)

Chapter 7: Handling Competing Goals With Game Trees

  1. A simple animation of the Minimax algorithm (Shaul Markovitch)

Chapter 8: Communicating With Natural Language

  1. Course Introduction - Stanford NLP
  2. ALICE chatbot

Chapter 9: Identifying Intelligence

  1. Super Intelligence Nick Bostrom (Talks at Google)
  2. How to Create a Mind Ray Kurzweil (Talks at Google)
  3. Singularity is Science Fiction Noam Chomsky (Nikola Danaylov)

Chapter 10: Conclusions and Where to Go from Here

  1. Elon Musk: 'Artificial Intelligence is Mankind's Biggest Threat' (Rubin Report)
  2. Bill Gates, Elon Musk and Robin Li on the threat of AI, China's AI "Apollo" Project (Singularity Videos)

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