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Exploring the Maze: A Comparative Study of Path Finding Algorithms for PAC-Man Game
Haneya, Hala Balbaid, Hanin Asrar, Manal
Haneya, Hala
Balbaid, Hanin
Asrar, Manal
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2024-03-21
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Abstract
Artificial Intelligence (AI) has become an integral part of our lives, finding applications across various industries. Search algorithms play a crucial role in AI. This paper focuses on the comparison of different search algorithms within the context of path-planning in the UC Berkeley’s PAC-Man’s game. The algorithms under consideration include Depth-First Search (DFS), Breadth-First Search (BFS), Uniform Cost Search (UCS), Iterative Deepening Depth First Search (IDDFS), and A⇤ Search. The objective is to identify the most effective algorithm in terms of path-finding performance. The study’s findings reveal that the A⇤ search algorithm outperforms the others in terms of score, cost, and node expansion, making it the most suitable choice for finding the shortest path in the PAC-Man’s game.