DeepStack: Ensembles for Deep Learning. DeepStack is a Python module for building Deep Learning Ensembles originally built on top of Keras and distributed under the MIT license. Installation pip install deepstack Stacking. Stacking is based on training a Meta-Learner on top of pre-trained Base-Learners. A deep stack is 200BB+. What it means to be deep stacked is you can call pot sized bets on every street and not be allin. A short stack will be allin w/2 or less pot sized bets a medium stack w/3. DeepStack is an AI server you can easily install, use completely offline or on the cloud for Face Recognition, Object Detection, Scene Recognition and Custom Recognition APIs to build business and industrial applications! DeepStack is an AI server you can easily install, use completely offline or on the cloud for Face Recognition, Object Detection, Scene Recognition and Custom Recognition APIs to build business and industrial applications! This documentation has been moved to Last updated 2 months ago 2 months ago.

1. Deepstack Ai Blue Iris
2. Deepstack Poker Venetian
3. Deepstack Docker
4. Deepstacks University

Expert-Level Artificial Intelligence in Heads-Up No-Limit Poker

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DeepStack bridges the gap between AI techniques for games of perfect information—like checkers, chess and Go—with ones for imperfect information games–like poker–to reason while it plays using “intuition” honed through deep learning to reassess its strategy with each decision.

With a study completed in December 2016 and published in Science in March 2017, DeepStack became the first AI capable of beating professional poker players at heads-up no-limit Texas hold'em poker.

DeepStack computes a strategy based on the current state of the game for only the remainder of the hand, not maintaining one for the full game, which leads to lower overall exploitability.

DeepStack avoids reasoning about the full remaining game by substituting computation beyond a certain depth with a fast-approximate estimate. Automatically trained with deep learning, DeepStack's “intuition” gives a gut feeling of the value of holding any cards in any situation.

DeepStack considers a reduced number of actions, allowing it to play at conventional human speeds. The system re-solves games in under five seconds using a simple gaming laptop with an Nvidia GPU.

The first computer program to outplay human professionals at heads-up no-limit Hold'em poker

In a study completed December 2016 and involving 44,000 hands of poker, DeepStack defeated 11 professional poker players with only one outside the margin of statistical significance. Over all games played, DeepStack won 49 big blinds/100 (always folding would only lose 75 bb/100), over four standard deviations from zero, making it the first computer program to beat professional poker players in heads-up no-limit Texas hold'em poker.

Games are serious business

Don’t let the name fool you, “games” of imperfect information provide a general mathematical model that describes how decision-makers interact. AI research has a long history of using parlour games to study these models, but attention has been focused primarily on perfect information games, like checkers, chess or go. Poker is the quintessential game of imperfect information, where you and your opponent hold information that each other doesn't have (your cards).

Until now, competitive AI approaches in imperfect information games have typically reasoned about the entire game, producing a complete strategy prior to play. However, to make this approach feasible in heads-up no-limit Texas hold’em—a game with vastly more unique situations than there are atoms in the universe—a simplified abstraction of the game is often needed.

A fundamentally different approach

DeepStack is the first theoretically sound application of heuristic search methods—which have been famously successful in games like checkers, chess, and Go—to imperfect information games.

At the heart of DeepStack is continual re-solving, a sound local strategy computation that only considers situations as they arise during play. This lets DeepStack avoid computing a complete strategy in advance, skirting the need for explicit abstraction.

During re-solving, DeepStack doesn’t need to reason about the entire remainder of the game because it substitutes computation beyond a certain depth with a fast approximate estimate, DeepStack’s 'intuition' – a gut feeling of the value of holding any possible private cards in any possible poker situation.

Finally, DeepStack’s intuition, much like human intuition, needs to be trained. We train it with deep learning using examples generated from random poker situations.

DeepStack is theoretically sound, produces strategies substantially more difficult to exploit than abstraction-based techniques and defeats professional poker players at heads-up no-limit poker with statistical significance.

Members (Front-back)

Michael Bowling, Dustin Morrill, Nolan Bard, Trevor Davis, Kevin Waugh, Michael Johanson, Viliam Lisý, Martin Schmid, Matej Moravčík, Neil Burch

low-variance Evaluation

Deepstack Ai Blue Iris

The performance of DeepStack and its opponents was evaluated using AIVAT, a provably unbiased low-variance technique based on carefully constructed control variates. Thanks to this technique, which gives an unbiased performance estimate with 85% reduction in standard deviation, we can show statistical significance in matches with as few as 3,000 games.

Abstraction-based Approaches

Despite using ideas from abstraction, DeepStack is fundamentally different from abstraction-based approaches, which compute and store a strategy prior to play. While DeepStack restricts the number of actions in its lookahead trees, it has no need for explicit abstraction as each re-solve starts from the actual public state, meaning DeepStack always perfectly understands the current situation.

Deepstack Poker Venetian

Professional Matches

We evaluated DeepStack by playing it against a pool of professional poker players recruited by the International Federation of Poker. 44,852 games were played by 33 players from 17 countries. Eleven players completed the requested 3,000 games with DeepStack beating all but one by a statistically-significant margin. Over all games played, DeepStack outperformed players by over four standard deviations from zero.

Heuristic Search

At a conceptual level, DeepStack’s continual re-solving, “intuitive” local search and sparse lookahead trees describe heuristic search, which is responsible for many AI successes in perfect information games. Until DeepStack, no theoretically sound application of heuristic search was known in imperfect information games.

The Venetian® Resort Las Vegas’ DeepStack Extravaganza I is set to kick off today, Feb. 2. The action-packed tournament series will play host to a total of 35 tournaments during the month of February, with more than $2 million in guaranteed prize money to be paid out along the way. The centerpiece of the exciting schedule is the $500,000 guaranteed $2,500 buy-in Card Player Poker Tour no-limit hold’em main event, which will run from Feb. 19-22.

The first day of action will feature two tournaments: a $20,000 guaranteed $400 buy-in no-limit hold’em ‘MonsterStack’ event and a $6,000 guaranteed $200 buy-in no-limit hold’em ‘survivor’ event, with start times of 11:10 a.m. and 6:10 p.m. local time.

Deepstack Docker

This series marks this ninth time that the CPPT has made its way to The Venetian Poker Room since first joining forces in 2013, with over $12.3 million in prize money awarded in the previous eight CPPT main events held at the property. All-time CPPT career earnings leader Jon Turner has won two of the CPPT Venetian events in recent years, cashing for a total of $737,858 in those title runs.

The 2021 DeepStack Extravaganza I features a variety of game options and formats, including bounty events, survivor tournaments, multi-day and single-day tournaments. Game options include no-limit hold’em, pot-limit Omaha, and PLO eight-or-better. Tournament buy-ins begin as low as $200 and range as high as the $2,500 buy-in for the CPPT main event, with affordable and exciting options for players at every level.

Another highlight of the series will be the $350,000 guaranteed Mid-States Poker Tour $1,100 buy-in no-limit hold’em event that will run from Feb. 4-6. Other standout events among the schedule include:

Deepstacks University

• $800 No-limit Hold’em UltimateStack with a $300,000 guarantee, Feb. 11-14
• $400 Pot Limit Omaha MonsterStack with a $40,000 guarantee, Feb. 21-23
• $600 No-limit Hold’em UltimateStack with a $200,000 guarantee, Feb. 25-28

The illustrious amenities and hospitality of The Venetian Resort, combined with their dynamic tournament atmosphere, make the DeepStack Extraganza I a must-play series for tournament poker fans. Make sure to make your way to The Venetian® Resort Las Vegas in February to get in on the action.

Here is a look at the complete schedule: