Analysis of A* Algorithm Optimization and Breadth First Search in the Water Teapot Game

Abstract

Artificial Intelligence (AI) is a branch of computer science that focuses on learning how computers can work or perform as well as humans or even better than humans. The development of artificial intelligence can be used as a benchmark for technological developments. Many problems can be solved using this artificial intelligence concept. One of them is a water jug ​​logic game. The water jugs problem is a game requiring converting a situation into another desired situation using a certain set of operations. The objective of this game is for players to develop their deductive reasoning skills by figuring out how to move x litters of water from one teapot to another. To accomplish this, they will refer to the beginning value that has to be filled in each teapot and the end value that needs to be filled in each teapot. Using the A* algorithm and the Breadth-First Search (BFS) algorithm, which both fall under the umbrella of artificial intelligence, it is possible to find a solution to this issue. The A* algorithm is a Best First Search algorithm that combines Uniform Cost Search and Greedy Best-First Search, while the Breadth-First Search algorithm is a graph search algorithm that performs a wide search at each level. This study analyzed the effectiveness of the A* and BFS algorithms in solving the water jug ​​logic problem, both from the number of steps and the time required for completion. The results of the tests were carried out, and it is known that the BFS algorithm is more effective than the A* algorithm because the BFS algorithm can provide a number of alternative solutions to the water jug ​​logic problem with various conditions.