This extra information is useful to compute the preference among the child nodes to explore and expand. It is named so because there is some extra information about the states. It is also called heuristic search or heuristic control strategy. Breadth First Search (BFS) and Depth First Search (DFS) are the examples of uninformed search. This kind of search techniques would search the whole state space for getting the solution. It is named so because there is information only about the problem definition, and no other extra information is available about the states. It is also called blind search or blind control strategy. They are explained in detail as given here − Uninformed Search There are two types of control strategies or search techniques: uninformed and informed. Difference between Uninformed and Informed Search Heuristic techniques are very useful because the search can be boosted when you use them. The method of using heuristic to lead the search in search space is called Heuristic Search. Thus, the use of heuristic narrows down the search for solution and eliminates the wrong options. You do not know exactly which solutions are correct and checking all the solutions would be very expensive. Most problems in artificial intelligence are of exponential nature and have many possible solutions. Heuristic is a rule of thumb which leads us to the probable solution.
In this chapter, you will learn in detail about it. Heuristic search plays a key role in artificial intelligence.
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