πŸ€‘ Blackjack Computer Betting Efficiency

Most Liked Casino Bonuses in the last 7 days πŸ’

Filter:
Sort:
BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Through the computer's trial and error it figured out which decisions are best for the player, given every possible combination of starting player hands and dealer​.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
HIGH STAKES BLACKJACK! - Double Up or Double Down!? (Online Casino)

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Professional gambler tests Keith Taft's David blackjack computer (also known as the Casey blackjack computer) for the computer's betting efficiency.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
Las Vegas Heist - The Covert BlackJack Computer That Beat Las Vegas - Full Documentary

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Blackjack 21 is a comparing card game between a player and a dealer, meaning players will compete against a dealer but PC Mobile device.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
Las Vegas Heist - The Covert BlackJack Computer That Beat Las Vegas - News 2

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Through the computer's trial and error it figured out which decisions are best for the player, given every possible combination of starting player hands and dealer​.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
Computer Roulette \u0026 Blackjack ACTION!!!!!

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Free Blackjack Games - Play blackjack FREE with our instant, no registration games. Enjoy 60+ of the best blackjack games (choose from many variants).


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
Online Blackjack High Roller Bets With VIP Table

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Casino Blackjack is an easy-to-understand and effective way to learn blackjack; the rules, the etiquette and ways to develop your game and eventually beat the.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
INSANE COMPUTER BLACKJACK SESSION! CLEANING THE WEBSITE OUT!

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Play the best free Blackjack game. Easy to read cards. If you are on a streak and need to leave your computer, no worries! Your fabulous.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
IT IS SO RIGGED! COMPUTER BLACKJACK SESSION!

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Blackjack 21 is a comparing card game between a player and a dealer, meaning players will compete against a dealer but PC Mobile device.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
£200 BIG BET BLACKJACK HANDS!! ⚠️(Online Casino)

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Professional gambler tests Keith Taft's David blackjack computer (also known as the Casey blackjack computer) for the computer's betting efficiency.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
Online Blackjack - Using the Martingale System (Real Money)

BN55TO644
Bonus:
Free Spins
Players:
All
WR:
30 xB
Max cash out:
$ 500

Play the best free Blackjack game. Easy to read cards. If you are on a streak and need to leave your computer, no worries! Your fabulous.


Enjoy!
Valid for casinos
Visits
Likes
Dislikes
Comments
HIGH STAKES Computer Blackjack!!

But that improvement is definitely a case of diminishing returns: the number of tests had to be increased 5x just to get half the variability. A higher fitness score for a strategy merely means it lost less money than others might have. Clearly, having a large enough population to ensure genetic diversity is important. The flat white line along the top of the chart is the fitness score for the known, optimal baseline strategy. Comparing the results from a GA to the known solution will demonstrate how effective the technique is. The other hints of quality in the strategy are the hard 11 and hard 10 holdings. In the case of a Blackjack strategy, the fitness score is pretty straightforward: if you play N hands of Blackjack using the strategy, how much money do you have when done? Because of the innate randomness of a deck of cards, many hands need to be played so the randomness evens out across the candidates. The first thing to notice is that the two smallest populations having only and candidates respectively, shown in blue and orange performed the worst of all sizes. During that run, about , strategies were evaluated. Once two parents are selected, they are crossed over to form a child. This works just like regular sexual reproduction β€” genetic material from both parents are combined. The three tables represent a complete strategy for playing Blackjack. Since the parents were selected with an eye to fitness, the goal is to pass on the successful elements from both parents. This is the very best solution based on fitness score from candidates in generation 0 the first, random generation :. The soft hand and pairs tables are getting more refined:. The hard hands in particular the table on the left are almost exactly correct. The idea of a fitness function is simple. The chart here that demonstrates how the variability shrinks as we play more hands:. Standard deviation is scaled to the underlying data. Genetic algorithms are essentially driven by fitness functions. As you might imagine, Blackjack has been studied by mathematicians and computer scientists for a long, long time. Given those findings, the fitness function for a strategy will need to play at least , hands of Blackjack, using the following rules common in real-world casinos :. There are a couple of observations from the chart. In fact, the coefficient of variation for , hands is 0. Using a single strategy, multiple tests are run, resulting in a set of fitness scores. Due to the house edge, all strategies will lose money, which means all fitness scores will be negative. By generation 33, things are starting to become clear:. The process of finding good candidates for crossover is called selection, and there are a number of ways to do it. Roulette Wheel Selection selects candidates proportionate to their fitness scores. Back in the s, a mathematician named Edward O. It works by using a population of potential solutions to a problem, repeatedly selecting and breeding the most successful candidates until the ultimate solution emerges after a number of generations. Each candidate has a fitness score that indicates how good it is. One simple approach is called Tournament Selection , and it works by picking N random candidates from the population and using the one with the best fitness score. We solve this by dividing the standard deviation by the average fitness score for each of the test values the number of hands played, that is. That evolutionary process is driven by comparing candidate solutions. There are a number of different selection techniques to control how much a selection is driven by fitness score vs. The X axis of this chart is the generation number with a maximum of , and the Y axis is the average fitness score per generation. In fact, it looks like a minimum of , hands is probably reasonable, because that is the point at which the variability starts to flatten out. Even though we may not know the optimal solution to a problem, we do have a way to measure potential solutions against each other. The variations from run to run for the same strategy will reveal how much variability there is, which is driven in part by the number of hands tested. To use the tables, a player would first determine if they have a pair, soft hand or hard hand, then look in the appropriate table using the row corresponding to their hand holding, and the column corresponding to the dealer upcard. The pairs and soft hand tables develop last because those hands happen so infrequently. But how many hands is enough? Oftentimes, crossover is done proportional to the relative fitness scores, so one parent could end up contributing many more table cells than the other if they had a significantly better fitness score. A pair is self-explanatory, and a hard hand is basically everything else, reduced to a total hand value. One of the unusual aspects to working with a GA is that it has so many settings that need to be configured. Neural networks are great for finding patterns in data, resulting in predictive capabilities that are truly impressive.

One of the great things about machine learning is that there are so many different approaches to solving problems. The lack of genetic diversity in those small populations results in poor final fitness blackjack computer, along with a slower process of finding a solution.

As it turns out, you need to play a lot of hands with a strategy to determine its quality. Could we see more withor more hands per test? Using such a strategy allows blackjack computer player to stretch a bankroll as far as possible while hoping for a run of short-term good blackjack computer.

Knowing that, the best possible strategy is the one that minimizes losses. A cell in the child is populated by choosing the corresponding cell from one of the two parents. One of the cool things about GAs is simply watching them evolve a solution.

And then the final generations are used to refine the strategies. To avoid that problem, genetic blackjack computer sometimes use blackjack computer the introduction of completely new genetic material to boost genetic diversity, although larger initial populations also help.

By measuring the standard deviation of the set of scores we get a sense of how much variability we blackjack computer across the set for a test of N hands. Population Size.

Of course. Knowing the optimal solution to a problem like this is actually very helpful. Imagine a pie chart blackjack computer three wedges of size 1, 2, and 5.

That score is calculated once per generation for all candidates, and can be used blackjack computer compare them to each other.

That optimal strategy looks something like this:. The columns along the tops of the three tables are for the dealer upcard, which influences strategy. Once this fitness score adjustment is complete, Roulette Wheel selection is used.

One of the problems with that selection method is that sometimes certain candidates will have such a small fitness score that they never get selected. Varying each of these gives different results. Here are two other approaches:. That means that if the same GA code is run twice in a row, two different results will be returned. By generation 12, some things are starting to take shape:. First, testing with only 5, or 10, hands is not sufficient. Once an effective fitness function is created, the next decision when using a GA is how to do selection. Reinforcement learning uses rewards-based concepts, improving over time. If you play long enough, you will lose money. The tall table on the left is for hard hands , the table in the upper right is for soft hands , and the table in the lower right is for pairs. The following items can be configured for a run:. The best way to settle on values for these settings is simply to experiment. Tournament selection has already been covered. That gives us something called the coefficient of variation , which can be compared to other test values, regardless of the number of hands played. If, by luck, there are a couple of candidates that have fitness scores far higher than the others, they may be disproportionately selected, which reduces genetic diversity. There will be large swings in fitness scores reported for the same strategy at these levels. The goal is to find a strategy that is the very best possible, resulting in maximized winnings over time. The fitness function reflects the relative fitness levels of the candidates passed to it, so the scores can effectively be used for selection. The source code for the software that produced these images is open source. Populations that are too small or too homogenous always perform worse than bigger and more diverse populations. With only 12 generations experience, the most successful strategies are those that Stand with a hard 20, 19, 18, and possibly That part of the strategy develops first because it happens so often and it has a fairly unambiguous result. Basic concepts get developed first with GAs, with the details coming in later generations. It reduces variability and increases the accuracy of the fitness function. The more hands played, the smaller the variations will be. Of course, in reality there is no winning strategy for Blackjack β€” the rules are set up so the house always has an edge. Running on a standard desktop computer, it took about 75 minutes. Finally, the best solution found over generations:. The first generation is populated with completely random solutions. A genetic algorithm GA uses principles from evolution to solve problems. As impressive as the resulting strategy is, we need to put it into context by thinking about the scope of the problem. The solution is to use Ranked Selection , which works by sorting the candidates by fitness, then giving the worst candidate a score of 1, the next worse a score of 2, and so forth, all the way up to the best candidate, which receives a score equal to the population size.