- #The rules of nine mens morris software
- #The rules of nine mens morris free
A mill may be broken and reformed repeatedly by moving a man back and forth.Again, this must be a man which is not in a mill, unless all of the opponent's men are in mills, in which case any man may be removed. As before, completing a mill allows a player to remove one of the opponent's men.After all the men have been placed, each turn consists of moving a cow to a vacant adjacent cell.A single placement may create more than one mill, but only one man may be removed.However, a man in a mill may not be removed unless all of the opponent's men are in mills, in which case any man may be removed. If a player forms a mill, he may remove (capture) one of the opponent's men from the board.
The aim is to create a 'mill': a row three men on any line drawn on the board. Each turn consist of placing a man on a vacant cell. The object of Nine Men's Morris is to capture at least 7 opponent's men or to block all opponent's men completely. The board is initially empty and each player has 9 men of his color 'in hand'. White moves first after which player's alternately move. Nine Men's Morris is played on a special board with 24 cells connected with lines indicating valid movements as in the diagram. with the symmetric ones.Nine Men's Morris is an abstract strategy board game for two players that emerged from the Roman Empire and persisted throughout Europe and beyond. The EXTENDED STATES DATASET contains all the states. The COMPLETE STATES DATASET contains all the states, without the symmetric ones. None of the states contained in this dataset is present in the Good Moves Dataset. It has been generated exploring the space of the game states applying random choices from a reachable configurations. The dataset consist of 2,085,613 states which are reachable through a finite sequence of legal moves starting from the initial empty board configurations. The EXPANDED DATASET contains all the data and the symmetric pairs. Therefore it contains states which are more unlikely to be reached during a match. The GAMING DATASET do not contains data coming from a regular match starting with an empty board. The COMPLETE DATASET contains all the data, without the symmetric pairs. Three version of the dataset are available: The moves contained in it could be different from the optimal one, however, it constitutes a good knowledge base, from which other AI system can learn to play the game.Īll the data have been generated making play an Artificial Intelligence called Deep Mill against other artificial intelligence and gathering the choices made by Deep Mill during the games. The dataset contains states both reachable and unreachable during a normal match, decreasing the probability of reaching a training state during a testing match. If all the symmetric states are explored, the dataset can reach 1,628,673 pairs. None of the states in the dataset is symmetric to any other, therefore anyone can handle the symmetries as he/she prefers. The dataset consist of 100,154 game states and as many good moves elaborated by an Artificial Intelligence for the game of Nine Men's Morris. 
/nine-mens-morris-5832e9223df78c6f6a460ac3.jpg "the rules of nine mens morris")
Further details can be found in the file LICENSE.txt Documentation (V 1.1.1)Ĭontains the functions used to manipulate the data.Ĭontains the functions used to establish the legality of a move.Ĭontains the functions used to create, load, save and use neural networks.Ĭontains the functions used to test the system according to different characteristics.Ĭontains the functions used to train a neural network system.Īdditional informations regarding the dataset can be found here: Good Moves Dataset (Matches Dataset) The system has been written in Python language, relying on the Lasagne, Theano and Numpy libraries.
#The rules of nine mens morris software
The results of this work have been published in IEEE Transactions on Games: įurther information can be found on the software website: Implementation
#The rules of nine mens morris free
Please feel free to contact him (a.galassi at ) or his thesis supervisors (Paola Mello, llo at, Federico Chesani federico.chesani at ) for further questions. It has been designed by Andrea Galassi, as part of his master thesis in Computer Science Engineering ("Ingegneria Informatica", in italian), and it has been improved as part of a successive work. It has been demonstrated that the system is capable to learn to play by the rules of the game, even if the knowledge of those rules has not been provided to it. Neural Nine Men's Morris (NNMM) is a software capable to build, train, test and use Deep Neural Networks which can be used for playing the game of Nine Men's Morris. Mello, "Can Deep Networks Learn to Play by the Rules? A Case Study on Nine Men's Morris," in IEEE Transactions on Games, vol.
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