You're reading from Artificial Intelligence with Python Your complete guide to building intelligent apps using Python 3.x

Product type Paperback

Published in Jan 2020

Publisher Packt

ISBN-13 9781839219535

Length 618 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Authors (2):

Prateek Joshi

Alberto Artasanchez

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Table of Contents (26) Chapters

Preface

1. Introduction to Artificial Intelligence

2. Fundamental Use Cases for Artificial Intelligence FREE CHAPTER

3. Machine Learning Pipelines

4. Feature Selection and Feature Engineering

5. Classification and Regression Using Supervised Learning

6. Predictive Analytics with Ensemble Learning

7. Detecting Patterns with Unsupervised Learning

8. Building Recommender Systems

9. Logic Programming

10. Heuristic Search Techniques

11. Genetic Algorithms and Genetic Programming

12. Artificial Intelligence on the Cloud

13. Building Games with Artificial Intelligence

14. Building a Speech Recognizer

15. Natural Language Processing

16. Chatbots

17. Sequential Data and Time Series Analysis

18. Image Recognition

19. Neural Networks

20. Deep Learning with Convolutional Neural Networks

21. Recurrent Neural Networks and Other Deep Learning Models

22. Creating Intelligent Agents with Reinforcement Learning

23. Artificial Intelligence and Big Data

24. Other Books You May Enjoy

25. Index

Is heuristic search artificial intelligence?

In Chapter 2, Fundamental Use Cases for Artificial Intelligence, we learned about the five tribes as defined by Pedro Domingos. One of the most "ancient" tribes is the symbolist tribe. At least to me, this fact is not surprising. As humans, we try to find rules and patterns in everything. Unfortunately, the world is sometimes messy and not everything follows simple rules.

This is the reason why other tribes emerged to help us when we don't have an orderly world. However, when our search spaces are small and the domain is limited, using heuristics, constraint satisfaction, and other techniques laid out in this chapter, is useful for this set of problems. These techniques are useful when the number of combinations is relatively small and combinatorial explosion is limited. For example, solving the traveling salesman problem is simple with these techniques when the number of cities is around 20. If we try to solve the...