Etymology and usage. Casino is of Italian origin; the root casa means a house. The term casino may mean a small country villa, summerhouse, or social club. During the 19th century, casino came to include other public buildings where pleasurable activities took place; such edifices were usually built on the grounds of a larger Italian villa or palazzo, and were used to host civic town functions.
Basic Slots- Basic slots, or straight slots are slot machines that have only one single payline and a static jackpot or a jackpot amount that does not change as progressive jackpots do. Bet Max - Bet max refers to the number of credits on a slot machine that a player can bet per spin.

A patron who inserts currency into a slot machine would satisfy the definition of “customer” in 31 C.F.R. § 103.64(b)(3), whether or not the patron wagers the currency. The rule that requires the Casinos to report suspicious transactions refers to customers. Partial Reinforcement and Gambling. This is applicable in the case of gambling at a slot machine, and feeling unable to stop. When a person gambles at a slot machine, they’re unaware of when they will win a certain consequential amount of money, how much money and time they will need to spend to achieve that, or even if they will ever win.

Captain Jack: On Green Chip recently, someone asked about slot machine advantage players and why he can't find anyone who is willing to talk about it. I gave a short reply, but I think it warrants further discussion. It goes back to the classic debate of AP Art v. Science. Any robot can count cards, but the ability to get away with it is where the art of the process comes into play. Being a successful card counter requires subterfuge and good casino comportment. Therefore, while many books have been written on how to count cards, blackjack is still offered in casinos and more players ultimately lose attempting to count cards than those who show a profit long term. You can have all the science you want, but if you don't get the art of card counting, you're doomed.

Conversely, there is no art to slot machine play. Step 1 - Press a button. Step 2 - See step 1. If someone were to write the comprehensive guide to beating all beatable slots, then there would be no barrier to entry to becoming a slot machine AP. For the most part, there is no casino heat. Since the EV you are manifesting is created by other players playing at a deeper -EV, the casino doesn't really care. The only negative force in the casino is other AP's. There lies the rub. In the same way you'd never want to educate your opponent (the casino) in blackjack, educating other AP's on machines creates negative expectation.

Fortunately, for slot AP's, there has never been a better time to be alive. Whereas 7-8 yrs ago, slot AP play was probably worth only a couple dollars an hour, now with the abundance of opportunities it is easily a six-figure annual income for those who practice it. The competition is cut-throat. There are a lot of pseudo-gangs which bully lone AP's at casinos and AP's should be wary of their surroundings when coming and going from a casino. If you do find a slots AP willing to teach you, he either doesn't know what he's giving away or he doesn't know that much to begin with. The best way to learn is to teach yourself.

Refinery: That's very sound reasoning. I've been somewhat annoyed by the lack of sharing in this area but your explanation makes a lot of sense. I hadn't been bothered to consider it too much because other than stumbling across something incredibly easy that's a quick win, I'm not sure I'm interested. How long could I realistically sit and push a button?

Vagabond: Not to mention some idiot out there is sharing photos on social media of slot AP’s he encounters in the wild.

Maverick: There were days when members formed their own working groups. One might call them gaming investment groups. I can remember when we met as teams and went off with cell phones until one of us spotted something worth a call. Then we all would meet at the designated casino. I can remember when we traded online information on almost a daily basis. This seems like it would be amenable to such an approach. Like then, members of the working group could be from all over the world -- not just the United States.

Originally published on bj21.com Green Chip, edited for this format.

I want to learn....
thanks for the article back to grinding Blackjack for a bit

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There is a particular tension at the heart of applied behavioral science: We make decisions based on our unique circumstances and context, and yet we also desire solutions that can help people make better decisions on a massive scale. When I talk about this conflict inside the walls of a bank (I’m head of behavioral design at Capital One), I often describe it as “math versus snowflake.”

Everyone is a snowflake. We view ourselves—our circumstances, our values, the stability of our employment, our financial identity—as completely unique. And yet, despite our uniqueness, it’s also true that there are a finite number of clear, prescriptive methods for bringing about certain behaviors—the math. If we want someone to save more, we can examine their income, expenses, debt, savings, and employments, and it becomes clear what we should prescribe.

While my qualitative research provides strong evidence that everyone is unique in important ways, I’ve had many debates with colleagues who emphasize that you “can’t outrun the math.” Both conclusions are right. Any prescribed steps a person may take to improve their financial situation must both be mathematically sound (they must lead to a desired outcome) and account for what is unique (or perceived as unique) about each person.

And therein lies the challenge: How do we nudge a snowflake to follow the math? And then, how do we sustainably nudge a million snowflakes? The answer may be machine learning.

Machine learning improves our ability to predict what person will respond to what persuasive technique, through which channel, and at which time.

At its simplest, machine learning consists of training an algorithm to find patterns in data. By identifying patterns, the algorithm predicts more accurately and then learns from those predictions to make (hopefully) even more accurate predictions. Importantly, special algorithms allow a machine to improve on its own, instead of requiring us to make conclusions about the data and then manually reprogram it. Machine learning improves our ability to predict what person will respond to what persuasive technique, through which channel, and at which time. Machine learning understands that each snowflake is unique and acts accordingly, on a massive scale.

The closer technology is to us, the more it’s about us

It’s worth thinking about why machine learning could be extremely valuable—and maybe even necessary—when nudging for good. Thanks to technology, we are moving from an age in which products and services connect us to and better manage our things (music, money, email, friends) to an age in which products and services are explicitly designed to help us achieve behavior-based goals. In other words, we are moving from the utility age to the augmentation age. Once a financial institution helps people protect, move, and access their money, it can help people behave in ways that are consonant with their wishes: staying on budget, building their credit, or saving for retirement, among many others. All of these things are more about behaviors people can do rather than the utility of money. They are about augmenting people’s ability to act in ways they know they should. They are about helping them be their best selves. I refer to this as the behavior change value proposition, where the core value exchanged isn’t the utility itself, but the outcome from behavior-based changes.

The implication is that if people invite positive influence, we need to scale our ability to influence them not just through marketing and acquisition, but through the entire product or service lifecycle, based on a value proposition of behavior change. It’s a two-part challenge: first, augment the person’s rational self by providing a decision engine that, using machine learning, finds insightful patterns in their life and prescribes the next step. Then, control a person’s irrational self: identify and target their unique combination of biases and heuristics they use to make decisions, and protect them from those biases.

Behavioral Explanation Of Slot Machines Jackpots

Money coaches, activity trackers