Machine Learning Arena: Creating an ML Based GamePublic
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We present a new game, “MLA: Machine Learning Arena”, in which the player’s goal is to train a machine learning agent to win a boxing match. The game features multiple phases, fully animated characters for the player to control, and machine learning integration. We tackled several technical and design challenges, including: 1) Communicating machine learning progress through UI elements to the user, 2) Training an effective model for the game agent despite poor training examples from users, 3) Explaining key ideas about machine learning to players with no background in the field. We conduct user testing with 27 players to determine if they feel that the ML is learning from them. We found that 85 percent of players were able to distinguish between a random agent and the trained agent.
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