Review of Various A* Pathfinding Implementations in Game Autonomous Agent

Abstract

Among many pathfinding algorithms, A* search algorithm is an algorithm that most commonly used in grid-based pathfinding. This is due to implementation of A* search which proven to be able to generate the optimal path in a relatively short time by combining two characteristics of Djikstra's and best-first search algorithm. In the implementation of A* search, the selection of heuristic function and data structure can affect the performance of the algorithm. The purpose of this research is to find the best heuristic function and data structure with regards of the performance in A* search implementation as a pathfinding algorithm in a 3D platform. In the experiment, some known heuristic functions and data structures will be tested on the various 3D platform with a different size and obstacle percentage. Based on experiment that have been done, euclidean squared distance is best heuristic function for 3D pathfinding problem, with regards of the implementation performance. In addition, we also found that binary heap is the best data structure to be implemented for 3D pathfinding problem, with regards of implementation performance.

List Point Marker Path Finding for Artificial Intelligence Movement in 3D Games

“…Pathfinding is closely related to the shortest path problem, in graph theory, which examines how to identify the path that best meets several criteria (shortest, cheapest, fastest, etc.) between two points in a large network [15], [16].…”

“…The advantage is, the number of nodes is smaller and the algorithm works very well. The disadvantage is that hierarchical pathplanners are difficult to implement [10], [15].…”

Comparison of Flow Field and A-Star Algorithm for Pathfinding in Tower Defense Game

“…The Flow Field Pathfinding algorithm has a time complexity of O(n2) notation; this notation is formed because the code checks all nodes on the grid in a nested if. A-Star algorithm uses mathematical equations and uses the lowest value overall as a pathway from the starting point to the endpoint [13]. The calculation of the lowest value is done using the heuristic formula [14] :…”