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Understanding the Breadth-First Search Algorithm

The breadth-first search (BFS) algorithm is a traversing algorithm where you start at a selected node (the source or starting node) and traverse the graph layer-wise, exploring the neighboring nodes (nodes that are directly connected to the source node). You then move towards the neighboring nodes in the next level.

In this chapter, you will learn about BFS while developing LinkedIn's connection feature. You will learn how second-degree connections can be computed by using the BFS algorithm.

In this chapter, we will cover the following topics:

Understanding the LinkedIn connection feature
Graph data structure
Queue data structure
The BFS algorithm
DFS versus BFS

Key benefits

Enter the world of Artificial Intelligence with solid concepts and real-world use cases

Make your applications intelligent using AI in your day-to-day apps and become a smart developer

Design and implement artificial intelligence in searches

Description

With the emergence of big data and modern technologies, AI has acquired a lot of relevance in many domains. The increase in demand for automation has generated many applications for AI in fields such as robotics, predictive analytics, finance, and more. In this book, you will understand what artificial intelligence is. It explains in detail basic search methods: Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search, which can be used to make intelligent decisions when the initial state, end state, and possible actions are known. Random solutions or greedy solutions can be found for such problems. But these are not optimal in either space or time and efficient approaches in time and space will be explored. We will also understand how to formulate a problem, which involves looking at it and identifying its initial state, goal state, and the actions that are possible in each state. We also need to understand the data structures involved while implementing these search algorithms as they form the basis of search exploration. Finally, we will look into what a heuristic is as this decides the quality of one sub-solution over another and helps you decide which step to take.

Who is this book for?

This book is for developers who are keen to get started with Artificial Intelligence and develop practical AI-based applications. Those developers who want to upgrade their normal applications to smart and intelligent versions will find this book useful. A basic knowledge and understanding of Python are assumed.

What you will learn

Understand the instances where searches can be used

Understand the algorithms that can be used to make decisions more intelligent

Formulate a problem by specifying its initial state, goal state, and actions

Translate the concepts of the selected search algorithm into code

Compare how basic search algorithms will perform for the application

Implement algorithmic programming using code examples

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