Uniform Cost Search vs. BFS Algorithm

Search Algorithms

Depth-First Search (DFS)

• DFS is used to traverse or search tree or graph data structures
• DFS starts exploring from the root node (or an arbitrary node of a graph, sometimes referred to as a 'search key')
• It follows a traversal strategy of exploring as far as possible along each branch before backtracking

Uniform Cost Search

• Uniform Cost search is equivalent to BFS algorithm when the cost of moving from node to node is the same
• Characteristic that makes Uniform Cost search different from DFS: it takes into account the cost of moving from node to node
• Primary goal: find the shortest path to the goal node by minimizing the total cost
• Gives maximum priority to the lowest cumulative cost when expanding nodes

Breadth-First Search (BFS)

• Searches breadthwise in a tree or graph
• Typically implemented using a queue data structure
• Decides which nodes to expand first based on their level (nodes at the current level are explored before moving to the next level)

Uninformed Search Algorithm

• Defining characteristic: doesn't use any additional information about the problem, making it blind to the goal
• Examples: DFS, BFS, Uniform Cost Search

GPS Navigation Systems

• One of the best algorithms used to find neighboring locations is Uniform Cost Search

Graph Traversal

• In an unweighted graph, the idea behind calculating the shortest path is to find the path with the fewest number of edges
• In a weighted graph, a search algorithm that takes into account the cost of each edge, such as Uniform Cost Search, is used