Coding and comparing different search algorithm outputs. (BFS, DFS, UCS)
We explore different routes to get from Kitchener to Listowel. By analyzing various search space methods we can indentify the advantages and disadvantages of each one.
Depth-First Search (DFS): DFS is an algorithm that explores a graph by visiting a branch as deeply as possible before backtracking. It's best used when you want to search deep into a tree or graph, and it's often employed in applications like maze-solving and topological sorting.
Breadth-First Search (BFS): BFS explores a graph by systematically visiting all nodes at a given depth level before moving on to deeper levels. It's ideal for finding the shortest path in unweighted graphs and for tasks where you need to explore neighbors before moving deeper, such as web crawling and network routing.
Uniform Cost Search (UCS): UCS is a graph search algorithm that selects nodes with the lowest cumulative cost to reach them, making it suitable for finding the shortest path in weighted graphs. It's particularly useful in scenarios where edge weights represent various costs, like GPS navigation systems and resource allocation problems.
Breadth-First Search (BFS) explores nodes in a graph level by level to find the shortest path, Depth-First Search (DFS) explores as far as possible along one branch before backtracking, and Uniform Cost Search (UCS) selects nodes with the lowest cumulative cost to reach them, prioritizing shorter paths.