Abstract
Role Playing Game (RPG) needs realistic Artificial Intelligence, pathfinding is one of the requirements to achieve it. One of the popular algorithm for pathfinding is A∗, but A∗ still has problem about its memory usage. Iterative Deepening A∗ (IDA∗) is an algorithm like A∗ that uses Depth First Search to prevent the large memory usage. This research develops a game that implements pathfinding method to enemy character using A∗ and IDA∗ algorithms to compare their memory and time usages for pathfinding. Heuristic function that used is Manhattan Distance. This research uses 3 different types of map (without obstacle, simple obstacle, and complex obstacle) with 3 different samples in each type of map as tool for comparing the memory and time usage by A∗ and IDA∗. The conclusion of this research are memory and time usage for A∗ and IDA∗ is affected by the size of map (node quantity), position of the obstacles on map, and the obstacle quantity. Then, IDA∗ Algorithm is generally better than A∗ in case of memory and time usage especially if the map doesn't have any obstacle, but IDA∗ can be worse if the enemy character and player are at the parallel position that covered by obstacle.
Published Version
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