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I'm currently writing a 2D game in Javascript using the HTML5 <canvas> element. It's coming along very nicely, but i have run into a problem.
The level design for my game is a grid (so path cost moving from one cell to the north/south/east/west cell is 1) with various obstacles occupying various locations in the grid – a lot like a maze, but with a lot more wiggle room. Each individual level is on the order of 400 × 200 cells.
I'm trying to implement an enemy that will seek out the player no matter where they might be, but i'm having trouble trying to translate one of the various path-finding algorithms to fit my situation. Most of the ones i've come across (like A* and Dijkstra) seem to be best suited to 3D or much more complicated 2D situations. I was wondering if it is possible to dramatically simplify these algorithms to better suit my purposes, or if something like the depth-first search would be a more efficient alternative given the level size.
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A* pathfinding algorithm is arguably the best pathfinding algorithm when we have to find the shortest path between two nodes. A* is the golden ticket, or industry standard, that everyone uses. Dijkstra's Algorithm works well to find the shortest path, but it wastes time exploring in directions that aren't promising.
Dijkstra's algorithm is used for our fastest path algorithm because it can find the shortest path between vertices in the graph. The coordinates on the arena are considered as the vertices in the graph.
The two most commonly employed algorithms for directed pathfinding in games use one or more of these strategies. These directed algorithms are known as Dijkstra and A* respectively [RusselNorvig95].
The A* Algorithm Like Dijkstra, A* works by making a lowest-cost path tree from the start node to the target node. What makes A* different and better for many searches is that for each node, A* uses a function f ( n ) f(n) f(n) that gives an estimate of the total cost of a path using that node.
A* is a very common 2D pathfinding algorithm. It might take a little time to wrap your head around what's happening if pathfinding is unfamiliar, but it's not terribly complex. You may just be looking at someone else's example code that's been developed for a more complex application than you intend. There's a good tutorial for understanding the algorithm here.
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