# Is a * faster than Dijkstra?

**is A* faster than Dijkstra**. I understand how

**Dijkstra**Algorithm and A* Algorithm work and that A* is the general case of

**Dijkstra**. It is commonly said that A* finds the solution

**faster**which kind of makes sense as you use a heuristic that speeds up the process / reduces the effective branching factor.

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Likewise, people ask, is a * better than Dijkstra?

It is said theoretically that A* is **better than Dijkstra**. Using A*, 108.475 ms, expanded 255135 nodes. Noticing that in A*, we expanded less 1405 nodes. However, the time to compute a heuristic is much more **than** that saved.

Additionally, wHAT IS A * pathfinding? A* is often used for the common **pathfinding** problem in applications such as video games, but was originally designed as a general graph traversal algorithm. It finds applications in diverse problems, including the problem of parsing using stochastic grammars in NLP.

Accordingly, what is the difference between Dijkstra and A *?

A* is just like **Dijkstra**, the only **difference** is that A* tries to look for a better path by using a heuristic function which gives priority to nodes that are supposed to be better than others while **Dijkstra's** just explore all possible paths.

Does Dijkstra's algorithm always work?

**Dijkstra's algorithm works** correctly, because all edge weights are non-negative, and the vertex with the least shortest-path estimate is **always** chosen. However, a small example in Figure 4.17 shows that **Dijkstra's algorithm** fails to find the shortest paths when negative weights exist.