| Summary: | This article presents an application of Minimax strategy and game theory to implement the Linja mobile game. This game theory strategy applies collaborative learning to determine the winner of a game between two opponents, thus determining the optimal move in complex environments. In the development of the collaborative game, different game learning scenarios are proposed where competition between a player and the machine, and competitions against other players, intervene. In the learning process, moves are proposed that allow the maximum gain and the minimum loss among the competitors. In this case, the methodological approach was carried out towards the move that allows maximizing the profit and minimizing the loss, based on the application of the Mini/Max algorithm in search of determining the optimal solution of the game. The process is obtained from the adaptation of mathematical models for the development of games, using specialized tools that support a multi-paradigm programming language working together with the tools that the same language provides and that potentially serve as a contribution to the development of the game. In the search for an intelligent and autonomous system. The intelligent system correctly finds the winner of a game, showing the course of the game move by move. The results show that the game developed with the Minimax strategy allows automatic learning in multiuser environments, correctly identifying the winner of a game, generating the most optimal route of the game from move to move.
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