In this episode, I speak with Tuomas Sandholm, Carnegie Mellon University Professor and, along with his PhD student Noam Brown, winner of a 2017 NIPS Best Paper award for the paper “Safe and Nested Subgame Solving for Imperfect-Information Games.”
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Tuomas and I dig into the significance of the paper, including a breakdown of perfect vs imperfect information games, the role of abstractions in game solving, and how the concept of safety applies to gameplay. We discuss how all these elements and techniques are applied to poker, and how the algorithm described in this paper was used by Noam and Tuomas to create Libratus, the first AI to beat top human pros in No Limit Texas Hold’em, a particularly difficult game to beat due to its large state space. This was a fascinating interview that I’m really excited to share with you all. Enjoy!
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Mentioned in the Interview
- Check out @ShirinGlander’s Great TWIML Sketches!
- Safe and Nested Subgame Solving for Imperfect-Information Games
- Optimized Markets
- John Nash
- Theory of Games and Economic Behavior
- Register for the RE•WORK Deep Learning Summit here!
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