In the initial placement, DeepNash tried all possible placements so that the opponent could not see through the pattern, and in moving pieces, he randomly repeated seemingly the same movements so as not to reveal his hand to the opponent. In addition, DeepNash showed surprising behavior in the initial placement and movement of frames. Don't let your opponent's strategy fool you. However, the basic idea of the Nash equilibrium where DeepNash converges is to ``do not change your strategy''. It is a game in which bluffing, meticulous information gathering, and bargaining with the opponent are important due to the rule that the identity of the opponent's piece is revealed only when it touches the opponent's piece. It is a rule that you win if you take all the opponent's moveable frames or take the opponent's F. B and F are immovable, only minor (3) can handle B. Except for 2, you can move up, down, left and right by 1 square. Basically, the larger number can take the smaller piece, but the weakest S can win only against the strongest 10 and take 10. 10 is strong against 9, 2 is strong against S, etc. Each frame is assigned a symbol of S (1), 2 to 10, B, F, respectively Spy (S), Scout (2), Marshal (10), Bomb (B), Flag (F), etc. It seems that it is finished in a style that is very difficult for opponents to capture.Īn example of a Stratego board looks like this. It is said that it will converge to the Nash equilibrium that it will be in a non-negotiable state. Newly learned DeepNash adopts an algorithmic idea called 'Regularized Nash Dynamics (R-NaD)', and its play style is 'If each other always makes the most rational choice, each other will make a strategy. Therefore, DeepNash has adopted a new approach based on game theory and model-free deep reinforcement learning. It is difficult to use this technique in the 'imperfect information game' in which important information is hidden. In ``Complete Information Games'' such as chess, shogi, and Go, where all piece information is open to the public, a method called `` game tree search'' is used, which considers and analyzes the patterns of finger moves. Generally speaking, the maximum number of game records for chess is 10 to the 120th power or more, and the maximum number of game records for shogi is 10 to the 220th power or more. Like shogi and chess, it is a game in which pieces with different roles are placed on the board and moved, but the main feature is that ``the identity of the opponent's piece is not known until the pieces touch each other.'' Since the initial placement can be decided as you like, the strategy including psychological factors such as bluffing is important. Stratego is a one-on-one turn-based board game. Mastering the game of Stratego with model-free multiagent reinforcement learning | Science Learning by AI was very difficult because the information was hidden, but ' DeepNash ' developed by DeepMind cleared it and reigned in the top 3 online games of all time. Unlike chess and Go, where players can grasp the identity of the pieces from the beginning, AI has mastered the board game `` Stratego '' that fights while hiding the identity of each other's pieces. 13:21:00 DeepMind's AI ``DeepNash'' masters military shogi ``Stratego'' that hides the identity of the frame
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