Heuristic Pathfinding Algorithms in Video Games Indepth Analysis and Performance

Abstract

The creation of artificial intelligence in video games is mostly dependent on heuristic pathfinding algorithms. The ability to move of the agent is one of the biggest obstacles in the construction of accurate artificial intelligence (AI) in video games. Before the A* algorithm emerged as a provably optimum solution for pathfinding, several search algorithms, including Dijkstra’s algorithm, the bread first search algorithm, and depth first search algorithm, were developed to tackle the shortest route issue. Since its inception, it has drawn the interest of several scholars who have decided to work on it. This paper provides an in-depth analysis of these algorithms, focusing on their development, evolution, and performance. Beginning with an overview of classical algorithms like A*, the paper explores recent advancements and optimizations. Performance metrics and practical applications are discussed, with case studies from contemporary video games. This analysis highlights the balance between computational efficiency and path optimality, guiding future developments in game AI.