Graphs and networks
Search algorithms are different ways of asking: where should we look next?
A graph can represent roads, friendships, dependencies, game maps, web links or choices. Search algorithms give us systematic ways to move through those connections without relying on guesswork.
Unweighted search
If every edge counts the same, BFS and DFS are the natural starting point. They reveal reachability, connected components and traversal order.
Weighted paths
If edges have costs, distances or times, algorithms such as Dijkstra, A* and Bellman-Ford help compare possible routes.
Whole-network questions
Some problems are not about one route. Floyd-Warshall asks for the best path between every pair of vertices at once.
Start exploring
Breadth-first and depth-first search
Compare two fundamental ways to explore a graph: spreading out layer by layer or following one path deeply before backtracking.
LiveDijkstra's algorithm
Find shortest paths when every edge has a non-negative weight by repeatedly locking in the nearest unsettled vertex.
LiveA* search
Use a heuristic to guide shortest-path search towards a goal instead of exploring equally in every direction.
Planned algorithm pages
These pages now have a simple explanation page so the section has a proper shape. The interactive tools can be built one at a time.