The 15 Puzzle is a classic sliding-tile puzzle where scrambled tiles need to set in the proper order. The tiles are set in a 4x4 grid with one position empty, and tiles can only be moved by sliding into the empty space. It is a one-player, perfect-information game: the player always knows the exact position of tiles and possible moves. This makes it a useful test of search algorithms, which automatically play out various moves and evaluate the result to find the best sequence of moves.
Challenges for AI Research
The 15 Puzzle is a version of the Sliding Tile Puzzle, which is an important test domain for heuristic search.
A heuristic is an estimation of the distance remaining from the current position in the game to the goal.
A state is a possible configuration of the tiles in the puzzle.
There are 16! possible configurations of the tiles in the 15 Puzzle. Half of these configurations are not solvable, and it is easy to tell whether or not a configuration can be solved. Even with 16!/2 remaining configurations that can be solved, there are still far more states than can be stored in memory in a computer.
Search algorithms look for the shortest (optimal) path of moves from the current state of the game to the goal.
A* finds the shortest possible path, but even on the 15 Puzzle, it is impossible to store all the states of the game in memory. Therefore, other variations of A* must be used to reduce memory requirements. An example is IDA*, which uses a technique called iterative-deepening.
Current techniques can find the shortest possible path in the 15 Puzzle, but larger versions of the sliding tile puzzle is still difficult.
Research History
The 15 Puzzle was invented in the late 1800s.
Dijkstra's algorithm for finding the shortest path in a graph was invented in 1959.
The search algorithm A* was invented in 1968, and improve on Dijkstra's algorithm by introducing the use of heuristics into the search.
Since then, many improvements to A* have been made, including strategies for pruning states that will not lead to the goal, and other methods of determining which paths to explore next.
The choice of heuristics is also another interesting research area. Heuristics are giving an estimate of the distance to the goal, but it is often difficult to come up with a very accurate estimate without already knowing the solution.
The 15 Puzzle is a classic sliding-tile puzzle where scrambled tiles need to set in the proper order. The tiles are set in a 4x4 grid with one position empty, and tiles can only be moved by sliding into the empty space. It is a one-player, perfect-information game: the player always knows the exact position of tiles and possible moves. This makes it a useful test of search algorithms, which automatically play out various moves and evaluate the result to find the best sequence of moves. Challenges for AI ResearchThe 15 Puzzle is a version of the Sliding Tile Puzzle, which is an important test domain for heuristic search.A heuristic is an estimation of the distance remaining from the current position in the game to the goal.A state is a possible configuration of the tiles in the puzzle.There are 16! possible configurations of the tiles in the 15 Puzzle. Half of these configurations are not solvable, and it is easy to tell whether or not a configuration can be solved. Even with 16!/2 remaining configurations that can be solved, there are still far more states than can be stored in memory in a computer. Search algorithms look for the shortest (optimal) path of moves from the current state of the game to the goal.A* finds the shortest possible path, but even on the 15 Puzzle, it is impossible to store all the states of the game in memory. Therefore, other variations of A* must be used to reduce memory requirements. An example is IDA*, which uses a technique called iterative-deepening.เทคนิคปัจจุบันสามารถค้นหาเส้นทางได้สั้นที่สุดในปริศนา 15 แต่รุ่นใหญ่กระเบื้องปริศนาเลื่อนได้ยังยาก ประวัติงานวิจัยปริศนา 15 ถูกคิดค้นในเพราะล่าช้าวิธีของไดค์หาเส้นทางสั้นที่สุดในกราฟถูกคิดค้นใน 1959 การค้นหาอัลกอริทึม A * คิดค้นใน 1968 และปรับปรุงในวิธีของไดค์ โดยแนะนำการใช้การลองผิดลองถูกค้นหาตั้งแต่นั้น มากให้ A มีการปรับปรุง รวมถึงกลยุทธ์สำหรับอเมริกาตัดที่จะไม่นำไปสู่เป้าหมาย และวิธีการอื่น ๆ ของการกำหนดเส้นทางที่ให้บริการต่อไปลองผิดลองถูกเลือกเป็นพื้นที่วิจัยอื่นที่น่าสนใจ ลองผิดลองถูกจะนำการประเมินระยะทางเพื่อเป้าหมาย แต่เป็นเรื่องที่ยากจะเกิดขึ้นกับการประเมินความถูกต้องมากโดยไม่ทราบการแก้ปัญหาแล้ว
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