Uninformed (Blind) Search

Uninformed search algorithms operate without any domain-specific knowledge about the problem. These algorithms do not use information such as the location of the goal or the proximity of states to the goal. Instead, they traverse the search tree systematically, evaluating nodes based solely on their position within the tree. This lack of guidance often results in brute-force exploration of the search space, examining every possible state until the goal is found.

Key Characteristics of Uninformed Search

1. No Heuristics: Relies purely on the structure of the search tree.

2. Exhaustive Exploration: Explores all possible nodes, making it complete but often inefficient.

3. General Applicability: Can solve any problem where the goal state can be identified.

Types of Uninformed Search Algorithms

1. Breadth-First Search (BFS)

2. Depth-First Search (DFS)

3. Depth-limited Search (DLS)

4. Iterative Deepening Depth-First Search (IDDFS)

5. Uniform Cost Search (UCS)

6. Bidirectional Search (BDS)

Let's take a closer look at all these types.