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)

Greedy BFS

In the Revisiting the navigation application section, you learned that a heuristic value is a property of the node, and it is a guess, or estimate, of which node will lead to the goal state quicker than others. It is a strategy used to reduce the nodes explored and reach the goal state quicker. In greedy BFS, the heuristic function computes an estimated cost to reach the goal state. For our application, the heuristic function can compute the straight-line distance to the goal state, as follows:

Figure 11

As you can see, in the preceding diagram the initial state is the Bus Stop. From the Bus Stop node, we have one channel, which is the Library node. Let's suppose that we're at the Library now; from the Library node, there are three child nodes: the Car Park, the Bus Stop, and the Student Center. In real life, we'd prefer to go to the Car Park, because...