Beginning Artificial Intelligence with the Raspberry Pi

ISBN-13: 9781484227428 / Angielski / Miękka / 2017 / 369 str.

Donald J. Norris

Opis

Using the Raspberry Pi as the computing platform, this book explores most of the major AI topics, including expert systems, machine learning both shallow and deep, fuzzy logic control and more. A series of projects will walk through how to implement the AI concepts. Minimal expense is needed as only a few sensors and actuators will be required.

Recenzje

"This book is a practical introduction to the field of artificial intelligence (AI) that can serve as either a primer to the subject or a companion to theoretical studies. ... Summing Up: Recommended. Lower- and upper-division undergraduates; professionals and practitioners." (J. M. Smith, Choice, Vol. 55 (6), February, 2018)

Spis treści

Chapter 1 title:  Introduction to Artificial Intelligence

• Explain what AI is and is not.  

• Establish why it is important and how it may be used  

• What is the state of AI today and how is it developing?

   

Chapter 2 title:  Basic AI Concepts

•  What is inference?

•  Introduce the concept of the expert system

•  What is machine learning?  Detail the various branches of ML.

• Is fuzzy logic really fuzzy?  Explain how it is used in real-world control situations

  

Chapter 3 title:  The Raspberry Pi and an Expert System

• Introduce the Prolog language 

• Demonstrate a simple expert system running on the Raspberry Pi with Prolog

• Simple Q&A demonstration using an expert system

  

Chapter 4 title:  Some Simple AI Games •  Introduce the Python language to implement several games demonstrating AI behavior

•  Paper, rock, scissors

•  Nim (or sometimes referred to as pepple pickup)

•  The "wave" demonstrating emergent behavior

•  "Tic-Tac-Toe" and an expert system

  

Chapter 5 title:  Fuzzy Logic Control Project

•  Use Prolog to create FL sets

•  Integrate expert system knowledge into the FL control algorithms

•  Demonstrate FL control using a Raspberry Pi with a light sensor and LED indicators

  

Chapter 6 title:  Machine Learning - Shallow

•  Explore shallow learning

•  Simple demonstration about learning a favorite color

•  Naive Bayesian decisions and decision trees

  

Chapter 7 title:  Machine Learning - Deep with Neural Networks•  Explore deep learning

•  Simple two-layer neural network

•  Neural network demonstration using Python

Chapter 8 title:  Machine Learning - Deep with Genetic Algorithms

•  Explore how to create a genetic algorithm

•  Implement a "longest-path" algorithm for a virtual robot

•  Demonstrate the algorithm using a Raspberry Pi controlled "Boe-bot" robotic car

Chapter 9 title:  Computer Vision 

•  What is computer vision and how is it related to AI?

•  Introduction to the Wolfram Language (WL) and Mathematica as run on the Raspberry Pi

•  Several CV demonstrations using WL/Mathematica using the PiCamera as well raw image data from the Wolfram Research servers

Chapter 10 title:  Subsumption

•  What is subsumption?

•  Explanation of a virtual subsumption robotic model

•  An actual subsumption demonstration using the Boe-bot robot from chapter 8.

O autorze

Donald J. Norris has a degree in electrical engineering and an MBA specializing in production management. He teaches undergrad and grad courses in the IT subject area at Southern New Hampshire University. He also created and teaches several robotics courses there. He has over 36 years of teaching experience as an adjunct professor at a variety of colleges and universities. Mr. Norris retired from civilian government service with the U.S. Navy, where he specialized in acoustics related to nuclear submarines and associated advanced digital signal processing. Since then, he has spent more than 22 years as a professional software developer using C, C#, C++, Python, Node.js and Java, as well as 5 years as a certified IT security consultant. Mr. Norris started a consultancy, Norris Embedded Software Solutions (dba NESS LLC), that specializes in developing application solutions using microprocessors and microcontrollers. He likes to think of himself as a perpetual hobbyist and geek and is always trying out new approaches and out-of-the-box experiments. He is a licensed private pilot, photography buff, amateur radio operator, and avid runner.

Blurb

Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more!

AI in action will be demonstrated using the Python language on the Raspberry Pi.  The Prolog language will also be introduced and used to demonstrate fundamental AI concepts.  In addition, the Wolfram language will be used as part of the deep machine learning demonstrations.

A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book.