On Using Monte-Carlo Tree Search to Solve Puzzles

Solving puzzles has become increasingly important in artificial intelligence research since the solutions could be directly applied to real-world or general problems such as pathfinding, path planning, and exploration problems. Selecting the best approach to solve puzzles has always been an essential issue. Monte-Carlo Tree Search (MCTS) has surged into popularity as a promising approach due to its low run-time and memory complexity. Thus, it is required to know how to employ this method to solve the puzzles.