Pluribus Poker
Like many other recent AI-game breakthroughs, Pluribus relied on reinforcement learning models to master the game of poker. The core of Pluribus’s strategy was computed via self-play, in which the. The new code, named Pluribus, can play — and beat — six-handed no-limit hold ’em (NLH). The software defeated professional poker players in two formats, one with five AIs and one human opponent and the other with one AI and five humans. Carnage Mellon University published in Science magazine the 10 000 poker hands played by Pluribus in 6 max no limit holdem against 10 pros. Indeed the impact is so important that the researchers have.
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I am a Research Scientist at Facebook AI Research working on multi-agent artificial intelligence. My research combines machine learning with computational game theory.
Pluribus Poker Bot Github
I have applied my research to making the first AI to defeat top humans in no-limit poker. With my CMU advisor, I created Libratus and Pluribus, which decisively defeated top human poker professionals in Human vs. Machine competitions. Libratus received the Marvin Minsky Medal for Outstanding Achievements in AI. Pluribus was on the cover of Science Magazine and was a runner-up for Science's Breakthrough of the Year for 2019. I was also named one of MIT Tech Review's 35 Innovators Under 35.
Pluribus Poker Paper
Pluribus Poker Science
I received a PhD in computer science from Carnegie Mellon. Before CMU, I worked at the Federal Reserve Board in the International Financial Markets section, where I researched algorithmic trading in financial markets. Before that, I developed algorithmic trading strategies.
Pluribus Poker Ai
Contact information: noamb@cs.cmu.edu