what is uninformed search in ai

What is Uninformed Search in AI? Understand in Simple Hindi

Uninformed Search is a basic but important search technique in Artificial Intelligence (AI). We use Uninformed Search techniques when solving a problem where we know the starting point but have no additional information about how to reach the destination. People often ask, what is uninformed search in AI and why is it important in AI—so let's understand it in detail.

Uninformed Search is also called Blind Search because it doesn't provide any specific hints or details to quickly reach a target node or goal. This type of search algorithm simply systematically explores the given states. This process is similar to a person groping their way through an unknown path.

Examples of Uninformed Search include (especially) the following:

• Breadth-First Search (BFS): systematically explores all possibilities at each level.
• Depth-First Search (DFS): exhaustively explores a single path or branch until it reaches a solution or a dead end.
• Uniform Cost Search: In this, only the cheapest path is pursued, taking into account the path cost.

None of these techniques uses any additional information or heuristics. Therefore, they are called 'uninformed'. In AI systems, these are suitable for problems where we know all the data or possibilities but not the direction.

Tips: When and why to choose uninformed search?

If you have all the possibilities (states) to solve a problem but no specific guidance or hint, uninformed search algorithms are best suited. To better understand the concepts, you can read more at Wikipedia: Search Algorithm.

Helpful Example

Suppose you need to solve a maze, but you don't have a map—in this case, uninformed search algorithms would be the best option!