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Artificial Intelligence with Python

You're reading from   Artificial Intelligence with Python A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781786464392
Length 446 pages
Edition 1st Edition
Languages
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Introduction to Artificial Intelligence FREE CHAPTER 2. Classification and Regression Using Supervised Learning 3. Predictive Analytics with Ensemble Learning 4. Detecting Patterns with Unsupervised Learning 5. Building Recommender Systems 6. Logic Programming 7. Heuristic Search Techniques 8. Genetic Algorithms 9. Building Games With Artificial Intelligence 10. Natural Language Processing 11. Probabilistic Reasoning for Sequential Data 12. Building A Speech Recognizer 13. Object Detection and Tracking 14. Artificial Neural Networks 15. Reinforcement Learning 16. Deep Learning with Convolutional Neural Networks

Building a maze solver


Let's use the A* algorithm to solve a maze. Consider the following figure:

The # symbols indicate obstacles. The symbol o represents the starting point and x represents the goal. Our goal is to find the shortest path from the start to the end point. Let's see how to do it in Python. The following solution is a variant of the solution provided in the simpleai library. Create a new Python file and import the following packages:

import math 
from simpleai.search import SearchProblem, astar 

Create a class that contains the methods needed to solve the problem:

# Class containing the methods to solve the maze 
class MazeSolver(SearchProblem): 

Define the initializer method:

    # Initialize the class  
    def __init__(self, board): 
      self.board = board 
      self.goal = (0, 0) 

Extract the initial and final positions:

        for y in range(len(self.board)):
            for x in range(len(self.board[y])):
          ...
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