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Tuomas Sandholm

artificial intelligence researcher
1 appearance ·5 ideas explored ·Wikipedia ·✓ verified

Tuomas Sandholm is the Angel Jordan University Professor of Computer Science at Carnegie Mellon University and a serial entrepreneur with a research focus on the intersection of artificial intelligence, economics, and operations research.

Across 1 conversation, Tuomas Sandholm ranges across collusion, imperfect information, Nash equilibrium. Libratus defeated top human players in Texas Hold'em, marking a milestone in AI's ability to handle imperfect information games. Nash equilibrium in poker involves both strategy and belief definitions, complicating AI's decision-making process.

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For the specialist
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Libratus' success in poker without learning methods challenges the assumption that deep learning is necessary for all complex AI tasks.
Tuomas Sandholm: Poker and Game Theory
The dual role of Nash equilibrium in defining strategies and beliefs complicates AI's decision-making in games with hidden information.
Tuomas Sandholm: Poker and Game Theory
The introduction of new game representations for coalitional games improves computational feasibility, offering new avenues for game design.
Tuomas Sandholm: Poker and Game Theory
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NIPS 2017 Best Paper
by Thomas Sanholm
Depth-Limited Search for Imperfect Information Games
by Unknown
Automated Mechanism Design
by Michael Johanson
Meyerson-Satterthwaite theorem
by Roger Meyerson and Mark Satterthwaite
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