Book Image

Hands-On Artificial Intelligence for Search

By : Devangini Patel
Book Image

Hands-On Artificial Intelligence for Search

By: Devangini Patel

Overview of this book

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.
Table of Contents (5 chapters)

Summary

In this chapter, we looked at four basic concepts related to searching: the state, which is the condition of our search process; the node, which is used for building a search tree; the stack, which helps to traverse the search tree and decides the order in which the nodes are traversed; and recursion, which eliminates the need for an explicit stack. You also learned about DFS, which explores the search tree in a depth-first order.

In the next chapter, you'll learn about breadth-first search (BFS), which explores a search tree in a breadth-first order. See you there!