PATHFINDING PADA LINGKUNGAN STATIS BERDASARKAN ARTIFICIAL POTENTIAL FIELD DENGAN FLOCKING BEHAVIOR UNTUK NON-PLAYER CHARACTER FOLLOWER PADA GAME

Abstract

Artificial Intelligence in video games are an essential to provide a challenge to the players. One of them makes the character or Follower NPC (non-player character Follower) in video games such as human or animal behavior indeed. Among the many techniques in Artificial Intelligence, pathfinding is one of the popular techniques studied than the other.  In own pathfinding is to avoid obstacles that is one of the main problem. Algorithm which solves this problem is Astarpathfinding, but it has a disadvantage in determining way in the large area. AstarPathfinding requires high computing time. In this research, the proposed algorithm which is able to handle the pathfinding process by using the function attractive potential field of Artificial Potential Field to perform pathfinding to the purpose and the flocking behavior techniques to avoid the obstacle. Based on the test results through environments static simulation, it can be gotten that the proposed algorithm has a faster computation time than the comparison algorithm, Astarpathfinding algorithm.

Kata Kunci : Artificial Intelligence, Game, pathfinding, Artificial Potential Field, Flocking behavior