“Poker is the main benchmark problem for testing imperfect-information game solving capability… Multi-player games present additional challenges not present in two-player zero-sum games.”Study co-author Dr. Tuomas Sandholm, Professor of Computer Science, Carnegie Mellon University, in Newsweek
The world of bluffs and tells is the latest game to be dominated by an AI system. Algorithmic victories are well known in chess and GO, but until now, AI play has been limited to two parties, methodical rules and transparent play.
A new AI model called Pluribus is winning at Texas Hold’em, among the most popular forms of poker.
Rules are still at the centre of poker, but so is concealment and deception. Unlike games where opposing plays are shown, poker players use feints as a strategy while keeping their cards to themselves. It’s made more complex with six sets in the mix.
Pluribus is showing poker prowess of its own. It is completely immune to bluffing and has no intention-revealing ‘tells’ for fellow players to weigh.
The MIT Technology Review says Pluribus ‘bluffed like a seasoned pro.’
Pluribus played 5,000 hands with winning poker pros who had million-dollar games to their credit. Then it turned 10,000 hands with 13 other players and won again.
The MIT Technology Review story says practical applications extend far beyond the felt of the gaming table. Future iterations might include strategy-making for pricing or automated control systems, such as in self-driving vehicles.
- Making good calls with incomplete information lies at the centre of news judgment. It’s a very long path from these developments to machines making editorial choices but you can connect a line from here to there.
- This is the second AI model released this year labelled to be ‘too dangerous to release’ (the first was the text-generating transformer model GPT-2.) In this case, the concern was for an unfair advantage if playing unsuspecting poker companies online.
- Cynics may suggest this is a marketing ploy. Others say it is a responsible measure without withholding the scientific significance of the advance. Either way, it signals a higher state of performance from a new cohort of algorithms.
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