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Applying state of the art AI search algorithms to solve the Sokoban game automatically. Since Sokoban game itself is quite challenging due to its problem complexity, additionally, heuristic functions and deadlock detectors are applied. (Python)

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csdankim/MCTS_Sokoban

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Aritificial Intelligence Project

Iterative Deepening A*, Recursive Best First Search, and Monte-Carlo Tree Search for Sokoban Games

 

Abstract

As the final project, we implemented IDA*, RBFS and MCTS in order to solve Sokoban game which is the well-known single player game. Sokoban game is a big challenge in artificial intelligence study due to its problem complexity. So, we had to apply heuristic functions and deadlock detectors. All algorithms solved problems, but their performances are, of course, different. The result of this experiment shows the possibility to improve algorithms further by considering specific conditions of the environment of the game.

 

The Experiment Results & Discussion

Please see the report.

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Applying state of the art AI search algorithms to solve the Sokoban game automatically. Since Sokoban game itself is quite challenging due to its problem complexity, additionally, heuristic functions and deadlock detectors are applied. (Python)

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