Blackjack Game Research Articles

Playing Blackjack Using Computer Vision

The field of computer vision is rapidly evolving, with a focus on analyzing, manipulating, and understanding images at a sophisticated level. The primary objective of this discipline is to interpret the visual input from cameras and utilize this knowledge to manage computer or robotic systems or to generate more informative and visually appealing images. The potential applications of computer vision are wide-ranging and include video surveillance, biometrics, automotive, photography, movie production, web search, medicine, augmented reality gaming, novel user interfaces, and many others. This paper outlines how computer vision technology will be utilized to achieve a winning outcome in the game of Blackjack. The game of Blackjack has long captivated the attention of enthusiasts and players worldwide. One area of particular interest is the development of a winning strategy that maximizes the player's chances of success. With the advent of sophisticated computer algorithms and machine learning techniques, there is enormous potential for research in this area. This paper explores the game-winning strategies for Blackjack, with a particular focus on utilizing advanced analytical methods to identify optimal plays. By analyzing large data sets and leveraging the power of predictive modeling, we aim to create a robust and reliable framework for achieving consistent success in this popular casino game. We believe that this research avenue holds enormous promise for unlocking new insights into the game of Blackjack and developing a more comprehensive understanding of its intricacies.

Game theory--optimum strategy for drawing cards in 21 points

Blackjack is a popular casino poker game in which players make drawing decisions based on rules other than the size of their points. We found that despite the randomness of the card draw, blackjack is actually very mathematical and logical. By calculating probabilities and using game theory, we can allow players to make relatively "rational" decisions that maximize their expectations of winning, rather than relying solely on guesswork and vague feelings. Therefore, in this article, we built several models to simulate a blackjack game with different numbers of people. For players in each model, we give them a code that outputs the optimal decision, which helps them figure out the winning percentage (more specifically, the expectation, since once stakes are involved in multiplayer games, the winning percentage doesn't necessarily represent the expectation of winning money) for each decision, thus helping the player make a better decision.

Web Exclusive. Annals Story Slam - A Two-Year Long Blackjack Game: Decisions During COVID.

Web Exclusive. Annals Story Slam - A Two-Year Long Blackjack Game: Decisions During COVID.

A New Multi-Agent Reinforcement Learning Method Based on Evolving Dynamic Correlation Matrix

Multi-agent reinforcement learning approaches can be roughly classified into two categories. One is the agent-based approach which can be implemented in real distributed systems, though most approaches of this type cannot provide meaningful theoretical verifications. The other can be seen as the more formalized approach, which can provide theoretical results. However, most of current algorithms usually require unrealistic global communication, which makes them impractical for real distributed systems. In this article, we propose a dynamic correlation matrix based multi-agent reinforcement learning approach where the meta-parameters are evolved using an evolutionary algorithm. We believe that our approach is able to fill the gap between the two kinds of traditional multi-agent reinforcement learning approaches by providing both agent-level implementation and system-level convergence verification. The basic idea of this approach is that agents learn not only from local environmental feedback, i.e., their own experiences and rewards, but also from other agents’ experiences. In this way, the agents’ learning speed can be increased significantly. The performance of the proposed algorithm is demonstrated on a number of application scenarios, including blackjack games, urban traffic control systems and multi-robot foraging.

Misunderstanding the behavior priming controversy: Comment on Payne, Brown-Iannuzzi, and Loersch (2016).

There has been considerable controversy around the limits and reproducibility of so-called "behavior" priming effects. Payne, Brown-Iannuzzi, and Loersch (2016) reported a series of 6 experiments on the effects of primes on participants' bets in a simulated blackjack game, and claimed that their findings not only establish the reality of behavior priming beyond dispute, but also demonstrate that this form of priming has the crucial hallmark of occurring outside participants' awareness and control. I describe a statistical model that does not distinguish automatic and controlled processes, but which nonetheless reproduces Payne et al.'s (2016) results and hence shows that their conclusions are unwarranted. Payne et al.'s (2016) experimental task and within-subjects design provide little insight into why some behavior priming studies have proven difficult to replicate. (PsycINFO Database Record

Did I do that? The association between action video gaming experience and feedback processing in a gambling task

The association between action video game experience and the neural correlates of feedback processing related to positive and negative outcomes was examined in a virtual Blackjack game in combination with event-related brain potentials (ERPs). The behavioral data revealed that the frequency of various outcomes was not related to action gaming experience, indicating that the associations between action gaming experience and the ERP correlates of feedback processing are unlikely to result from variation in motivation or skill related to the Blackjack game between the gamers and non-gamers. The ERP data revealed that action gaming experience was not related to the processing of positive feedback related to wins, or negative feedback for losses that resulted from the joint action of the player and dealer. In contrast, action gaming experience was associated with a reduction in the amplitude of the ERPs elicited by negative feedback wherein the loss resulted from the direct action of the individual (i.e., busts). Together these data may indicate that action gaming is associated with a reduced sensitivity to feedback related to negative outcomes resulting from the direct action of the individual.

Blackjack Game using Object Oriented Programming Methodology and Python

In this paper, it has been described how to implement the Blackjack game using Object Oriented Programming in the programming language Python. Object oriented programming is a programming technique which involves dividing the program into classes which have attributes (data) and methods (functions). Objects are basically instances of classes. By using Object Oriented Programming one can get several benefits such as ease of maintainability and code reuse. General Terms Blackjack, Python, Object Oriented Principles, Classes and Objects.

Gamble on gaze: Eye movements reflect the numerical value of blackjack hands.

We used a novel task-a blackjack game that naturally involves mental summation of numerical values-to investigate the role of attention in the mental number line (MNL) and to provide insight into the ecological validity of this representational format. By analyzing the spatial position of participants' spontaneous, task-irrelevant eye movements, we avoided some of the limitations of previous research on the MNL, in which the findings could be attributed to task-specific factors such as the use of overt spatial cues. In two experiments, we found that eye movements along the horizontal axis reflected the overall numerical value of participants' hands, with smaller-value hands eliciting fixations toward the left of the screen and larger-value hands eliciting fixations toward the right. This pattern held even when controlling for the number of cards in the hand and the value of the card most recently dealt-suggesting that the effects were driven by mental summation of values, not merely by the processing of serial order or individual numbers. Vertical eye movements, in contrast, reflected hand value less reliably. In showing that spontaneous eye movements along the horizontal axis track the magnitude of internally computed sums in an ecologically relevant task, our findings provide evidence for a dynamic MNL that supports magnitude-driven shifts of attention and that may be recruited during everyday forms of numerical reasoning.

Optimal betting sizes for the game of blackjack

We develop the theory of Kelly and Thorp for determining optimal bet sizes for blackjack by incorporating two vital, practical considerations. We first address the necessary requirement that only a finite number of plays may transpire. Further, we seek to maximize risk-adjusted returns, which are often a more likely criterion that players subscribe to. We show that the ratio of return to bet size is approximately proportional to the ratio of return to drawdown, and is a reasonable proxy for risk-adjusted returns. Thus, bet sizes that maximize this measure or its marginal increase are reasonable choices for maximizing risk-adjusted returns in the case of a finite number of plays. Theoretical analysis and computer simulation show that the alternative choices presented for bet sizes are much more conservative than the Kelly-Thorp theory suggests, and hence make sense in practice. In principle, the analysis and results here also apply to money management problems for investment as well as more generalized cumulative resource allocation considerations involving risk.

The Impact of Sexual Arousal on Sexual Risk-Taking and Decision-Making in Men and Women.

Sexual arousal has emerged as an important contextual feature in sexual encounters that can impact safer-sex decision-making. We conducted two experiments that investigated the effects of sexual arousal among male and female participants. Experiment 1 (N=144) examined the impact of sexual around on sexual health decision-making. Sexually explicit and neutral video clips as well as hypothetical romantic scenarios were used to evaluate the effects of sexual arousal on sexual risk-taking intentions. Men and women who reported higher levels of sexual arousal also displayed greater intentions to participate in risky sexual behavior (e.g., unprotected sex with a new sex partner). Experiment 2 (N=122) examined the impact of sexual arousal on general risk-taking, using the same videos clips as in Experiment 1 and a modified version of a computerized Blackjack card game. Participants were offered a chance to make either a risky play or a safe play during ambiguous conditions. Increased sexual arousal in Experiment 2 was associated with impulsivity and a greater willingness to make risky plays in the Blackjack game. These findings suggest that, in situations where there are strong sexually visceral cues, both men and women experiencing strong sexual arousal may have lower inhibitions and may experience impaired decision-making. This phenomenon may have an impact during sexual encounters and may contribute to a failure to use appropriate prophylactic protection.

The effects of age on the neural correlates of feedback processing in a naturalistic gambling game.

We examined age-related differences in the spatiotemporal distribution of event-related brain potentials (ERPs) related to feedback processing in a virtual blackjack game. The behavioral data revealed that older adults were less risk seeking than younger adults both within and across trials. Age-related differences were observed in the amplitude of several ERP components (P2-FN-P3a, P3a, slow wave activity) related to feedback processing. These components were localized to the anterior and posterior cingulate, the occipital cortex, and the inferior and medial frontal cortices. The effects of aging on the ERPs ranged from 200-2,000 ms after feedback onset. Our findings indicate that aging affects the activity of a distributed neural network that underpins processing the valence and motivational significance of feedback related to risky decisions.

Beyond the FN: A spatio-temporal analysis of the neural correlates of feedback processing in a virtual Blackjack game

Studies using event-related brain potentials (ERPs) to examine feedback processing in gambling tasks have focused almost exclusively on components elicited between 200 and 500ms after feedback over the frontal-central region of the scalp (i.e., P2, feedback negativity (FN), and P3a). In contrast, studies examining the functional neuroanatomy of feedback processing reveal activation in a distributed network that includes the anterior and posterior cingulate, the lateral and medial orbitofrontal cortex, the occipital cortex, and the basal ganglia. In the current study, we used ERPs in combination with spatial principal components-massive univariate analysis and distributed source analysis to examine the time course, topography, and neural generators of ERPs elicited in a virtual Blackjack game from 0 to 2000ms after feedback was delivered. The ERP data revealed the P2–FN–P3a complex, as well as, broadly distributed transient and slow wave activity that was sensitive to the magnitude and valence of an outcome. The ERPs reflected activation in the anterior and posterior cingulate, in addition to the occipital, temporal and medial frontal cortices. These data demonstrate that ERPs can provide valuable insight into the timing of neural recruitment within a distributed cortical network during the first two seconds of feedback processing.

The Ernst triadic model: A good start?

Studies using event-related brain potentials (ERPs) to examine feedback processing in gambling tasks have focused almost exclusively on components elicited between 200 and 500 ms after feedback over the frontal-central region of the scalp (i.e., P2, feedback negativity (FN), and P3a). In contrast, studies examining the functional neuroanatomy of feedback processing reveal activation in a distributed network that includes the anterior and posterior cingulate, the lateral and medial orbitofrontal cortex, the occipital cortex, and the basal ganglia. In the current study, we used ERPs in combination with spatial principal components-massive univariate analysis and distributed source analysis to examine the time course, topography, and neural generators of ERPs elicited in a virtual Blackjack game from 0 to 2000 ms after feedback was delivered. The ERP data revealed the P2–FN–P3a complex, as well as, broadly distributed transient and slow wave activity that was sensitive to the magnitude and valence of an outcome. The ERPs reflected activation in the anterior and posterior cingulate, in addition to the occipital, temporal and medial frontal cortices. These data demonstrate that ERPs can provide valuable insight into the timing of neural recruitment within a distributed cortical network during the first two seconds of feedback processing.

Casinos, casino size, and crime: A panel data analysis of Michigan counties

Abstract Growth in legal gaming in the United States over the past quarter century or so is well-documented. One important factor fueling this growth was the passage of the Indian Gaming Regulatory Act of 1988, which permitted Native American tribes to establish, under agreements or “compacts” with the states in which they are located, casinos offering what is known as Class III gaming: slot machines, blackjack, roulette, and other games. Since the passage of the Act, there have been 21 Native American casinos established in Michigan. Also, three non-Native American casinos opened in Detroit in 1999 and 2000. This growth in the number of casinos has sparked a wide-ranging debate over the social and economic impacts of casino development. The purpose of this research is to focus on the crime issue in the broader casino debate. We investigate the impact of these Michigan casinos on the rates of burglary, robbery, larceny and motor vehicle theft (property crimes) in casino host counties as well as in nearby counties. We employ a panel data set with annual observations on all 83 Michigan counties for the period 1994–2010. The dataset includes crime rates taken from the FBI crime data series, variables for the presence of a casino in a county or in a nearby county, the scale of a casino's operations as measured by revenues, and a variety of control variables suggested by the broader literature investigating the factors that determine crime rates generally. Our results suggest that in most cases the property crime rates studied are not affected by the presence or size of a casino in a county or in a nearby county. The largest such impact, which is negative, is for motor vehicle theft. The size of a casino does have a small positive effect on the motor vehicle theft rate.

Optimal Betting Sizes for the Game of Blackjack

We develop the theory of Kelly and Thorp in analyzing the optimal bet sizes for blackjack by incorporating the practical considerations of players wherein only a finite number of plays shall occur as well as pursuing maximizing risk-adjusted returns. We show that the ratio of return to bet size is approximately proportional to the return / drawdown ratio and is a reasonable proxy for risk-adjusted returns. Thus, bet sizes that maximize this measure or its marginal increase are also reasonable choices. Both theoretical analysis and computer simulation show that these alternative choices of bet sizes are much more conservative compared to what the Kelly-Thorp theory suggests and makes sense in practice. In principle, the analysis and results here also apply to money management problems for investment as well as more generalized cumulative resource allocation considerations involving risk.

Librarians and Code Year

As soon as I became editor of the Accidental Technologist, I thought of a column on Codecademy's program. Code Year is interesting not only for its unique online educational model but also because of the way librarians have organized a community around it. I met Andromeda Yelton at ALAs 2012 Midwinter conference, where she helped run an informal meeting of librarians participating in Code Year and organize an official ALA interest group around the event. She holds a BA in Mathematics from Harvey Mudd, an MA in Classics from Tufts, an MLS from Simmons, and works for Gluejar.inc, an innovative company set to unglue e-books by purchasing their rights and re-releasing them under Creative Commons licensing. As an active member of LITA and a co-chair of the Code Year Interest Group, she seemed like the perfect person to write a column explaining the program and its benefits.--Editor What if you could write a program to make bulk edits to thousands of MARC records with a single click? What if you could change the way your whole catalog looks--even if it's proprietary software that doesn't let you change the HTML? (1) What if you could write your own mobile web site to display your historical photographs to people throughout the community, in the very locations those photos were taken? (2) What if you could explain to your systems folks exactly what you needed because you could talk their language--and what if you didn't even have to ask, because you could do the work yourself? Questions like these--alternately practical, innovative, and empowering--are motivating librarians to learn to write software. There are many resources out there for people who want to learn to code: web sites, books, and classes (both free and paid). However, one that's been getting a lot of attention from librarians lately is Code Year, from codecademy.com. If you sign up at http://codeyear.com (it's free), Codecademy sends you a new programming lesson each week. The lessons are relatively short, build sequentially, and tie into projects for extra practice. Code Year is part of the gamification trend, so it awards badges for the successful completion of lessons and other milestones; it also makes it easy to share your progress on social networks. This free, bite-sized, rewarding approach--plus a splashy publicity campaign when it launched in January--got many dozens of librarians to sign up. What kinds of things can you learn through Code Year? The first 12 weeks were an introduction to JavaScript, a programming language used to create dynamic web content. The lessons covered the syntax of the language and traditional programming concepts like loops, functions, and variables. Extra projects, such as building a blackjack game, let people apply their knowledge. Code Year has now moved into an introduction to HTML and CSS. While it hasn't combined these languages yet, I expect it will down the line, enabling students to produce complete, interactive web pages. Because Code Year is built on the Codecademy platform, though, it's possible to learn many more things. This platform supports interactive lessons in JavaScript, Python, and Ruby. In addition, it allows creators to build their own lessons. At least one librarian has been taking advantage of this; one of the community-submitted lessons teaches how to build a JavaScript program to manipulate MARC records (http://www .codecademy.com/courses/marc-viewer). In my experience Codecademy is quick to respond to feedback, so if you'd like to beta test lessons to make them more beginner-friendly, or create your own lessons to share what you know, they want to hear from you. SO HOW DOES THIS CODE THING WORK, ANYWAY? I've been talking in generalities about code so far; I'd like to give a specific example. I'm going to walk you through a bit of jQuery I wrote for my employer's web site, http://unglue.it. jQuery is a derivative of JavaScript that simplifies some of the syntax, especially for the functions web developers use most. …

Something to Lose and Nothing to Gain

The current investigation explores how power and stability within a social hierarchy interact to affect risk taking. Building on a diverse, interdisciplinary body of research, including work on non-human primates, intergroup status, and childhood social hierarchies, we predicted that the unstable powerful and the stable powerless will be more risk taking than the stable powerful and unstable powerless. Across four studies, the unstable powerful and the stable powerless preferred probabilistic over certain outcomes and engaged in more risky behaviors in an organizational decision-making scenario, a blackjack game, and a balloon-pumping task than did the the stable powerful and the unstable powerless. These effects appeared to be the result of the increased stress that accompanied states of unstable power and stable powerlessness: these states produced more physiological arousal, a direct manipulation of stress led to greater risk taking, and stress tolerance moderated the interaction between power and stability on risk taking. These results have important implications for the way social scientists conceptualize the psychology of power and offer a theoretical framework for understanding factors that lead to risk taking in organizations.

HOW LONG CAN YOU ENJOY BLACKJACK WITH 100 CHIPS?

Gambling-related research has implications in financial area understandings and applications. Researches in this area usually focus on pathology, risk-taking, decision-making and addiction. Few works have been done to demonstrate the distribution of the playing time before players go bankrupt. One problem is that it is difficult to get statistics in real world gambling. In this paper, we do simulations in a Blackjack game with a selected strategy. We find the distribution of playing time before players lose a certain amount of money as a power law distribution, indicating the existence of very long playing time players. We also find that double is the most important factor that causes the fat tail. Comparison shows that when removing double, split and three to two payoff, Blackjack goes back to a random walk. The increase of the number of decks somewhat decreases the average playing time. Our results may have pathologic gambling intervention implications.

Self-esteem and risky decision-making: An ERP study

Self-esteem, a value one places on oneself, influences one's cognitive, emotional and behavioral responses across various situations. In the case of risky decision-making, high self-esteem (SE) individuals rely on their positive self-views and tend to be less defensive in response to a risky task; low SE individuals, on the contrary, tend to have fewer accessible positive resources and thus, are more prone to risk-aversion. While past studies have provided evidence for a link between self-esteem and a behaviorally-risky response, no study has explored the relation between self-esteem and the electrophysiological correlates of risky response. Therefore, the current study investigated the correlates of risky decision-making in high SE compared to low SE participants using event-related potentials (ERP) technology in 28 undergraduate students playing a blackjack game. The results showed that there was no difference between the high SE participants and the low SE participants with respect to the behavioral assessments of the risk-taking decision-making. However, for the electrophysiological data, we observed that the amplitude of P2 (150–300 ms) was more positive in the high SE participants compared to the low SE participants over the central-posterior scalp region. Dipole source analysis indicated that this positive component was generated in posterior cingulate cortex (PCC). These findings suggest that the high SE participants experienced more emotional signals than the low SE participants during decision-making.

Neurobiological correlates of problem gambling in a quasi-realistic blackjack scenario as revealed by fMRI

In the present study we obtained functional magnetic resonance imaging (fMRI) data in occasional gamblers (OG) and problem gamblers (PG) during a quasi-realistic blackjack game. We focused on neuronal correlates of risk assessment and reward processing. Participants had to decide whether to draw or not to draw a card in a high-risk or low-risk blackjack situation. We assumed PG would show differences in prefrontal and ventral striatal brain regions in comparison to OG during risk assessment and due to the winning or losing of money. Although both groups did not differ in behavioral data, blood oxygen level dependent (BOLD) signals in PG and OG significantly differed in thalamic, inferior frontal, and superior temporal regions. Whereas PG demonstrated a consistent signal increase during high-risk situations and a decrease in low-risk situations, OG presented the opposite pattern. During reward processing as derived from contrasting winning vs. losing situations, both PG and OG groups showed an enhancement of ventral striatal and posterior cingulate activity. Furthermore, PG demonstrated a distinct fronto-parietal activation pattern which has been discussed to reflect a cue-induced addiction memory network which was triggered by gambling-related cues.