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Artificial intelligence computers beat the world’s leading poker players

Two poker program computers beat the world’s leading poker players at Texas Hold’em Poker. TResearchers at the University of Alberta announced their program DeepStack beat human professional poker players in the game earlier today. The victory is a growing list of achievements the machines are stacking up against human players.

The computers that beat the world’s Leading Poker Players, used sophisticated algorithms to beat their human opponents. Solving a problem in the game of Poker with a computer requires the design of an algorithm.

The Computers beat the world’s leading poker players use simple concept

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The concept of the algorithm is the unifying concept of the theory of computability, without which little or nothing makes sense. In order to ascertain more clearly what is and is not to count as an algorithm, in addition to saying that an algorithm is an unambiguous, finite series of steps which eventually terminates with an output.

The researchers explained that the artificially intelligent computers that beat the world’s leading poker players emerged when the architecture and program fit together. They explained the process in which DeepStack anticipated moves of its opponents in a press conference.

Computers beat the world’s leading poker players: “smarter” than the best?

They said the machines beat the world’s leading poker players acted as if they had theaters of the mind in which the user plays a significant part in the production on the screen.

They enable the theater, we create on screen, in artificial intelligence pioneer Alan Kay’s provocative term, the “user illusion, ” which mirrors what we have in mind as we attempt to conceptualize and analyze the problems we find interesting.

A sentient computer simulates something when it represents, in one or more respects, that thing’s behavior or characteristics. The representation need not be exact, nor must it be done at the same speed as the original.

These computers that beat poker players work on an old age principle

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Deepstack operated on the same principle, while playing. While we might not usually think of a word processing document on a computer screen as a simulation, a moment’s reflection reveals that is what it is.

Deepstack simulates how poker moves would appear if played. The tiny picture elements on its screen, called “pixels,” are used to simulate both the images of the card movements and the processing environment that allows the machine to manipulate the moves.

The researchers said Deepstack is so smart it can serve as a word processor one moment,
an art historian illustrating Florentine linear perspective the next, a biologist illustrating the double helix structure of DNA the next.

The  Deepstack amplifies our understanding enables us to make connections, to see things that we almost certainly would miss otherwise.

We can look at things from different angles, in varying lights, against different backgrounds, and thereby generate new insight into even what is very old. It gets more difficult when the simulation is something as difficult to characterize adequately as thinking.

Artificially intelligent Computers beat the world’s leading poker players are fast gaining attention in the world of cognition and machine learning. Earlier last year, Google’s artificially intelligent machine defeated the world’s leading professional player in the ancient Chinese game of Go!

IBM’s Deep Blue has been playing chess with world’s top seeded players since the 90s. The machines seem to be winning so far and it seems for now, the future belongs to them!

This post first appeared on TechDigg, please read the originial post: here

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Artificial intelligence computers beat the world’s leading poker players


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