![]() Notably, say the authors, this performance was achieved without deploying any search methods, a key ingredient for many milestone AI achievements in board games in past. It won against all bots and achieved a highly competitive level of play against human expert Stratego players on Gravon, an internet gaming platform and the largest online platform for Stratego. DeepNash was tested against various state-of-the-art Stratego bots and human expert players. ![]() Role-playing board games often have individual character pieces that you can move across the board. Many board games also use dice which introduces an element of chance. Secondly, you often have game pieces (like the pieces in chess, dominoes, and checkers). At the core of DeepNash is a reinforcement learning algorithm, “R-NaD.” To make DeepNash, Perolat and team combined R-NaD with a deep neural network architecture to learn a strategy that plays at a highly competitive level. Firstly, you usually play on a board or a set playing area. ![]() This new method resulted in a bot called DeepNash that achieved human expert-level performance in the most complex variant of the game, Stratego Classic. Here, Julien Perolat and colleagues introduce a novel method that allows an AI for learning to play the game. Currently, it is not possible to use imperfect information search techniques to master Stratego. An “imperfect” information game (in which some aspect of play is hidden from opponents), Stratego poses key challenges to AI researchers because of the many complex aspects of its structure, including having more possible states than another well-researched imperfect information game: no-limit Texas Hold’em poker. For many years, the Stratego board game – which tests one’s ability to make relatively slow, deliberative, and logical decisions sequentially – has constituted one of the next frontiers of AI research. This represents an “extraordinary result that the Stratego community did not believe would have been possible with current techniques,” say the study’s authors. A newly developed AI agent called “DeepNash” learned to play Stratego, one of the few board games AI has not yet mastered, at a human expert level, researchers report.
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