Compare different pathfinding algorithms in action! Watch how A*, Dijkstra, BFS, and DFS explore the search space to find paths from start to goal.
Each algorithm has different strengths and use cases. Watch how they explore the search space differently to find paths.
Type: Informed Search
Guarantees: Optimal path (with admissible heuristic)
Complexity: O(b^d) where b is branching factor, d is depth
Use Case: When you need the shortest path and have a good heuristic
Type: Uninformed Search
Guarantees: Optimal path
Complexity: O((V + E) log V) with binary heap
Use Case: When you need shortest path without heuristic knowledge
Type: Uninformed Search
Guarantees: Optimal path (unweighted graphs)
Complexity: O(V + E)
Use Case: Simple pathfinding in unweighted graphs
Type: Uninformed Search
Guarantees: No optimal path guarantee
Complexity: O(V + E)
Use Case: Graph traversal, finding any path quickly