You're reading from Artificial Intelligence By Example Acquire advanced AI, machine learning, and deep learning design skills

Product type Paperback

Published in Feb 2020

Publisher Packt

ISBN-13 9781839211539

Length 578 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Author (1):

Denis Rothman

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Table of Contents (23) Chapters

Preface

1. Getting Started with Next-Generation Artificial Intelligence through Reinforcement Learning

2. Building a Reward Matrix – Designing Your Datasets FREE CHAPTER

3. Machine Intelligence – Evaluation Functions and Numerical Convergence

4. Optimizing Your Solutions with K-Means Clustering

5. How to Use Decision Trees to Enhance K-Means Clustering

6. Innovating AI with Google Translate

7. Optimizing Blockchains with Naive Bayes

8. Solving the XOR Problem with a Feedforward Neural Network

9. Abstract Image Classification with Convolutional Neural Networks (CNNs)

10. Conceptual Representation Learning

11. Combining Reinforcement Learning and Deep Learning

12. AI and the Internet of Things (IoT)

13. Visualizing Networks with TensorFlow 2.x and TensorBoard

14. Preparing the Input of Chatbots with Restricted Boltzmann Machines (RBMs) and Principal Component Analysis (PCA)

15. Setting Up a Cognitive NLP UI/CUI Chatbot

16. Improving the Emotional Intelligence Deficiencies of Chatbots

17. Genetic Algorithms in Hybrid Neural Networks

18. Neuromorphic Computing

19. Quantum Computing

20. Answers to the Questions

21. Other Books You May Enjoy

22. Index

Adding fulfillment functionality to an agent

A dialog can quickly become boring in everyday life and even more so in a chatbot. When we begin to guess everything that an interlocutor has to say, our mind slowly drifts away. We cannot help it. Humans are a curious species. Fulfillment will change the perspective of dialog. That is what I call purpose beyond the pragmatic approach that says fulfillment adds business logic to a dialog.

To make the dialog sustainable, even from a practical point of view, it has to excite the user enough to want it to come back and discover more about your chatbot beyond obtaining business information from it.

If you look fulfilling up in a dictionary, you will find that it means providing happiness or satisfaction, which is exactly the feeling of purpose you want your chatbot to convey.

That being said, there is work to do in order to reach that goal. Dialogflow provides a wide array of tools to reach fulfillment for the user, the designer...