Computers have beaten human world champions at chess and, earlier this year, the board game Go.

So far, though, they have struggled at the card table. So we challenged one AI to a game.

Why is poker so difficult? Chess and Go are "information complete" games where all players can see all the relevant information.

In poker, other players' cards are hidden, making it an "information incomplete" game. Players have to guess opponents' hands from their actions - tricky for computers.


Poker has become a new benchmark for AI research. Solving poker could lead to breakthroughs in all sorts of real life scenarios, from cybersecurity to driverless cars.

Scientists believe it is only a matter of time before AI once again vanquishes humans, hence our human-machine match-up in a game of Texas Hold'Em Limit Poker.

The AI was developed by Johannes Heinrich, researcher studying machine learning at UCL.

It combines two techniques: neural networks and reinforcement learning.

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Neural networks to some extent mimic the structure of human brains: their processors are highly interconnected and work at the same time to solve problems. They are good at spotting patterns in huge amounts of data.

Reinforcement learning is when a machine, given a task, carries it out, learning from mistakes it makes. In this case, it means playing poker against itself billions of times to get better.

Mr Heinrich told Sky News: "Today we are presenting a novel algorithm that has learned in a different way, more similar to how humans learn.

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"In particular, it is able to learn abstract patterns, represented by its neural network, that allow it to generalise to new and unseen situations."

This is a particularly beneficial property if we want to apply these methods beyond just poker to larger scale real world applications."

After two hours of quite defensive play, from the computer at least, we called it a draw.

In fact, this particular form of poker - two player, with limits on bets - was last year "weakly solved" in a lab by researchers at the University of Alberta. Its AI would at least break even against a human opponent over the long run.

But more complicated versions, with multiple players and unlimited bets, remain beyond AI. For now.