Book Image

Artificial Intelligence By Example - Second Edition

By : Denis Rothman
Book Image

Artificial Intelligence By Example - Second Edition

By: Denis Rothman

Overview of this book

AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.
Table of Contents (23 chapters)
21
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22
Index

Building the RL-DL-CRLMM

The full code of the RL-DL-CRLMM program is RL_DL.py. It is built on the knowledge and programs of the previous chapters and previous sections of this chapter.

The RL-DL-CRLMM contains three components:

  • A CRLMM convolutional network that will analyze each frame it receives from the webcam that is located right over the pieces of garment packs on the conveyor belt coming from the cutting section.
  • An optimizer using a modified version of the Z(X) described previously that plans how the assembly stations will be loaded in real-time.
  • An MDP that will receive the input of the optimizer function and schedule the work of the assembly stations. It also produces the modified Z(X) updated value of the weights of each assembly station for the next frame.

In the physical world, the conveyor belt transports the garment packs, a picture (frame) is taken every n seconds, and the RL-DL-CRLMM runs. The output of the RL-DL-CRLMM sends...