WOOT! My thesis, the bane of my existence for the last 2 years, is finally done! Its basically a review of the video game pathfinding field as well as presenting a novel grid map search technique: the spatial grid A*. The version linked below is the final draft that is being submitted to my faculty.
So I’ve recently completed my MSc thesis on video game pathfinding and I guess it’s a little weird for someone who spent the last year focusing on game AI and pathfinding to not actually spend much time blogging about it. I figured that I spent the time today and write a short post on optimizing the A* algorithm. The A* algorithm pretty much sums up video game pathfinding as a whole. Even advanced techniques like hierarchical pathfinding algorithm make use of A* in searching the various abstraction levels. So today I’m going to just discuss optimizing the algorithm, not a low level implementation but rather the some of the high level issues. I’m assuming that readers will have some degree of familiarity with the A* algorithm so I’m not going to waste time explaining it.
A*’s computational cost is primarily divided between two components, the heuristic function and the open list and so these are the components that I’m going to focus on. Continue reading “Optimizing the A* algorithm”