@thesis{thesis,
		author={Anggina  and Rusdi  and WAHYU },
		title ={PERBANDINGAN ALGORITMA A* DAN ITERATIVE DEEPENING A* PADA PENCARIAN RUTE TERPENDEK TERHADAP NON-PLAYER CHARACTER DALAM ROLE PLAYING GAME},
		year={2018},
		url={https://repository.unsri.ac.id/11993/},
		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}
		}