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The researchers pitted DeepRole against human players in more than 4, rounds of the online game "The Resistance: Avalon." In this game.
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Structured with innovative " deductive reasoning " that's added into an AI algorithm typically used when playing poker, the bot can reason with only partially observable actions. The bot then figures out whether or not a player is a friend or a foe. It can find cooperators in adversarial environments to win the game in a variety of team mixtures.


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Bots are better partners. Co-author, Max Kleiman-Weiner , MIT post-doctoral student at the Center for Brains, Minds, and Machines, and the Department of Brain and Cognitive Science added that "Humans learn from and cooperate with others, and that enables us to achieve together things that none of us can achieve alone. MIT news is featuring our work on AI agents that learn to find friends and foes in a multi-agent game.

To be presented at NeurIPS19 as a spotlight talk. This algorithm worked out how to play a game by repeatedly playing against itself. At each point in the game, CFR uses a ' game tree ' of lines and nodes that describe the potential future actions of all players. The next steps the researchers are looking at are developing ways to teach the bot to communicate with other players during a game by using simple text. Innovation AI.

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MIT Researchers Create Bot That Beats Humans at Multiplayer Hidden-Role Games

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Google's AI Wins Fifth And Final Game Against Go Genius Lee Sedol

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OpenAI vs HUMANS - AI vs 99.95% BEST PLAYERS 5v5 DOTA 2

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DeepRole's AI algorithm

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