DESIGN AND IMPLEMENTATION OF MINIMAL MEMORY ABSTRACTION METHOD FOR REALTIME PATHFINDING HANDLING IN ANGRY DOG GAME

Abstract

The development of increasingly complex computer games by presenting realistic graphics and sophisticated NPC (Non Player Character) requires developers to focus on developing aspects of graphics and artificial intelligence. Agent movement is an important element of the artificial intelligence aspect and the pathfinding strategy is a major part of agent movement. One of the learning algorithms that can be applied to solve realtime pathfinding problems is to use the minimal memory abstraction method. In this research, a pathfinding game called Angry Dog will be built and it will be tested whether the minimal memory abstraction method can be implemented in the Angry Dog game.