2021
AAAI
AAAI 2021
Analyzing Games with a Variable Number of Players
Abstract
Abstract We introduce a novel technique that uses a multi-headed neural network to analyze symmetric games with a variable number of players, where the number of participants falls in a specified range. We hypothesize that the payoffs in a game with x players are similar or related to the same game with x + 1 players, given a large value of x. With this hypothesis, we generalize prior work to analyze games with a large, variable number of players.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning
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Trend Setter
— Multi-Agent Systems
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Keyword Pioneer
— variable player
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio