Contract Bridge Research Articles

The sociology of bridge: Sport recognition for mind sports

The sociology of bridge: Sport recognition for mind sports The game of contract bridge, as we know it today, originated in the 20th century – but what lies ahead for bridge as a mind sport? Professor Samantha Punch, the academic behind “Bridge: A MindSport For All”, provides the answer. Bridge is a trick-taking card game played in partnership that has captured the hearts of hundreds of millions of players worldwide. Top players describe it as a “passion” and an “adrenalin rush.” It involves a very low level of chance and offers a new puzzle to solve every 71⁄2 minutes (the time spent per deal in tournament games). Yet bridge and other mind sports like chess have not gained widespread recognition as sports, and as such, do not stand on an equal footing with traditional sports.

Evolutionary reinforcement learning with action sequence search for imperfect information games

Deep Reinforcement Learning (DRL) has achieved remarkable success in perfect information games. However, when applied to imperfect information games like Contract Bridge, DRL faces challenges not only from unobservable partial information but also from the lack of efficient exploration. Although several Evolutionary Reinforcement Learning algorithms (ERLs) have harnessed Evolutionary Algorithms (EAs) to enhance exploration capabilities, the practical performance of EAs is limited either by the high-dimensional parameter space or possibly inaccurate guidance from value networks. In this paper, we introduce a novel ERL algorithm that employs the Particle Swarm Optimization (PSO) algorithm to search for superior action sequences, thereby aiding agents in exploring uncharted territory. We conduct the search in action space and evaluate action sequences through interactions with the environment to avoid the limitations of parameter space and value networks, respectively. The diverse experiences collected in the search and evaluation can boost the learning of the DRL agent. In addition, the action sequence search is executed only when the agent converges to local optima, which can reduce the overall cost of action evaluation and avoid influencing the optimization process of DRL. Through experimental comparisons conducted on Contract Bridge, our method demonstrates superior performance when compared with several state-of-the-art DRL and ERL algorithms. Furthermore, we utilize our method in the Bridge Competition of AAMAS 2023 Imperfect Information Card Games Competition and rank the first.

The Cognitive Benefits of Playing Contract Bridge in Elderly Patients with Dementia

The Cognitive Benefits of Playing Contract Bridge in Elderly Patients with Dementia

Short-run participation effects of tournament success: the case of online bridge

ABSTRACT We collected 330,180 observations of decisions by online contract bridge players of whether to play another tournament after just completing one. We compare the effect of the financial motive – the desire to continue playing when doing so is likely to bring financial reward – with that of the satisfaction motive – the cognitive effect induced by winning the tournament. We find that players are generally more likely to continue playing when playing well but that they are less likely to continue to play when they win a tournament: the satisfaction motive overcomes the financial motive. Understanding the interplay of such effects is crucial in increasing participation in skill-based tournaments.

Analysis of selected reinforcement learning applications in contract bridge

This paper presents an overview of four selected solutions addressing problem of bidding in card game of contract bridge. In the beginning the basic rules are presented along with basic problem size estimation. Brief description of collected work is presented in chronological order, tracking evolution of approaches to the problem. While presenting solution a short description of mathematical base is attached. In the end a comparison of solution is made, followed by an attempt to estimate future development of techniques.

H. Robert Gerberich

H. Robert Gerberich, 89, died Nov. 29, 2022, in Corpus Christi, Texas. “At the University of Rochester, Bob met fellow student Ronnie who became his wife of 65 years. His postdoctoral work was at Carnegie Mellon University. He was a research chemist at Celanese for his entire career, where he received several patents. Bob remained close to those he worked with throughout his retirement. He liked to work on household carpentry projects and play golf. However, his real passion was contract bridge. He was a member of the South Texas Bridge Association, an American Contract Bridge League affiliate. He played weekly and enjoyed traveling to tournaments, accumulating 4,000 master points.”—Tyler Dangerfield, grandchild-in-law Most recent title: Research chemist, Celanese Education: BA, chemistry, the College of Wooster, 1955; PhD, physical chemistry, University of Rochester, 1960 Survivors: Wife, Veronica; son, Michael; daughters, Lisa Jones and Sheila Caruso; four grandchildren To recognize your late

Artificial Neural Network Architectures for Solving the Contract Bridge

Contract Bridge is an intelligent game, which enhances the creativity with multiple skills and quest to acquire the intricacies of the game, because no player knows exactly what moves other players are capable of during their turn. The Bridge being a game of imperfect information is to be equally well defined, since the outcome at any intermediate stage is purely based on the decision made on the immediate preceding stage. One among the architectures of Artificial Neural Networks (ANN) is applied by training on sample deals and used to estimate the number of tricks to be taken by one pair of bridge players is the key idea behind Double Dummy Bridge Problem (DDBP) implemented with the neural network paradigm. This study mainly focuses on Cascade-Correlation Neural Network (CCNN) and Elman Neural Network (ENN) which is used to solve the Bridge problem by using Resilient Back-Propagation (R-prop) Algorithm and Work Point Count System.

Learning to Communicate Implicitly by Actions

In situations where explicit communication is limited, human collaborators act by learning to: (i) infer meaning behind their partner's actions, and (ii) convey private information about the state to their partner implicitly through actions. The first component of this learning process has been well-studied in multi-agent systems, whereas the second — which is equally crucial for successful collaboration — has not. To mimic both components mentioned above, thereby completing the learning process, we introduce a novel algorithm: Policy Belief Learning (PBL). PBL uses a belief module to model the other agent's private information and a policy module to form a distribution over actions informed by the belief module. Furthermore, to encourage communication by actions, we propose a novel auxiliary reward which incentivizes one agent to help its partner to make correct inferences about its private information. The auxiliary reward for communication is integrated into the learning of the policy module. We evaluate our approach on a set of environments including a matrix game, particle environment and the non-competitive bidding problem from contract bridge. We show empirically that this auxiliary reward is effective and easy to generalize. These results demonstrate that our PBL algorithm can produce strong pairs of agents in collaborative games where explicit communication is disabled.

Serious leisure activities and well-being of senior citizens: Case of contract bridge

Mind sports such as chess, go and contract bridge are extremely suitable for elderly people who want to engage into a real competition, make social contacts and maintain sharp cognitive performances. Stebbins (1992) introduced a term “serious leisure” to describe active leisure engagement with commitment and dedication, as opposed to “passive leisure” such as watching TV. Major (2001) identified three major types of benefits of serious leisure activities: sense of accomplishment (i.e., self-confidence, power, and control), health and fitness (i.e., physical benefits and stress relief), and social affiliation. The aim of this study was to explore motivation of senior citizens to engage in contract bridge, and to analyse selfreported benefits of the game regarding Major’s classification. We conducted eight semi-structured interviews with senior bridge players (over 65) in Zagreb bridge clubs. Interviews were conducted in face-to-face manner, and they were all audio recorded. Sample consisted of both male and female players who played bridge regularly in clubs for over five years. All participants confirmed that bridge significantly improved quality of their lives. Bridge contributed to their well-being by advancing social affiliation (communicating with people of all ages, finding new friends, getting social support, recognition and status, and going out of home), enchasing sense of accomplishment (learning, solving problems, competing, advancing, and winning), and mental fitness (staying intellectually fit), confirming benefits proposed by Major (2001) serious leisure model. Additionally, retired participants argued that bridge helped them in the transition period, providing basis for time structure and remaining the stable and fulfilling part of their lives. Findings of this research strongly suggest that contract bridge has power to work as a protective mechanism in seniors, due to its social, cognitive, and competitive benefits.

Issues in Emerging Area of Sports Law: Lex Sportivaa

While commentating upon the ‘law as a system of rules’, Salmond took ‘contract bridge’ as an example . At that time, Salmond would not have imagined that the rules of game would take such a proportion that it would necessitate a separate branch of study called ‘sports law’. Well, now sports law has a definite position in legal system and new sports law jurisprudence – lex sportiva is emerging. Increasing interaction between the sports and law has led to the development of sports law. Sports touches varied areas of law and the legal principles are adapted to the situation in sports. Areas of law like contract, tax, competition, discrimination share a boundary with sports when issues arises relating to performance of a contract or selection of a player on the basis of racial discrimination. There are larger issues of match-fixing, doping, and violence too. However, there is a haphazard development of sports law, reason being most of the rules being governed by various organization and as Salmond said ‘a person is subject to the rules of the game only when he plays the game.’ There are other areas like advertising rights, restraint clauses for players in contracts. The problem gets still larger when it comes to international sports where we already are under the porous roof of international law. The present article traces the development of sports law and points out key issues in sports law. The paper has five parts. First part deals with the introduction of sports law which includes the development of ‘sports law’ from ‘sports and law’; difference between amateur and professional sports, international sports law and global sports law. The second and third part discusses about the international sports federations and international sports organizations respectively. Fourth part discusses various issues involved in sports law and the paper ends with discussion on status of sports law in India.

Opera goer or Scrabble player: what makes a good translator?

How should you select a person to carry out a translation? One approach is to request a sample translation and to evaluate it by hand. Quality Estimation addresses the problem of evaluation at least for Machine Translation output as a prediction task. This approach facilitates low-cost evaluation of MT outputs without expensive reference translations. However, the prediction of human translation in this way is difficult due to its subtlety of expression. We aimed to find out whether the qualifications, hobbies or personality traits of a person could predict their proficiency at translation. First, we gathered information about 82 participants; for each one we established the values of 146 attributes via a questionnaire. Second, we asked them to carry out some Japanese-to-English translations which we scored by hand. Third, we used the attributes as input and the translation scores as output to train the J48 decision-tree algorithm in order to predict the score of a translator from their attributes. This was then evaluated using ten-fold cross validation. When limiting to professional translators in Experiment 6, the best F-score was with Wrapper selection (0.775). The result was statistically significant ($$p < 0.05$$p<0.05). This classifier also showed the second highest Precision on Good (0.813). The second best F-score (0.737) has the highest Precision on Good (0.909), using Manual feature selection. Once again this was significant ($$p < 0.05$$p<0.05). The results suggest that certain attributes affect the prediction; in addition to experience and qualifications in translating into the target language, interest in going to the Opera, playing Scrabble or Contract Bridge, or enjoyment of cryptic crossword puzzles are important factors as well.

Extended Leisure Experiences: A Sociological Conceptualization

ABSTRACTOur interest in this research reflection is to introduce what we call extended leisure experiences—activities that leisure participants engage in following the completion of a primary leisure activity. Our approach is largely descriptive and exploratory as we outline some properties of the concept and then flesh them out using observations gleaned from participation in the social worlds of contract bridge and music scenes. An understanding of extended leisure experiences will broaden our appreciation of how different phases of leisure activity are connected with one another and provide insight into how participants create meaning from their involvement in different pastimes.

A Bridge from Monty Hall to the (Anti-)Hot Hand: Restricted Choice, Selection Bias, and Empirical Practice

We show how classic conditional probability puzzles, such as the Monty Hall problem, are intimately related to a novel instance of selection bias found in Miller and Sanjurjo (2015). We explain the connection by way of the principle of restricted choice, an inferential rule from the game of contract bridge, which makes clear how information is revealed from the action of an optimizing opponent/partner. We propose that the principle is most naturally formalized with the odds form representation of Bayes rule, and show how it can make puzzles that are typically seen as paradoxical, intuitive. We illustrate how knowledge of such puzzles, and the principle of restricted choice, may help researchers avoid particular critical errors when designing experiments and analyzing data. Further, we provide examples in research domains that include the hot hand and Psi (ESP). Finally, we use restricted choice to illustrate the conceptual, and quantitative, relationship between a version of the well-known Berkson's Paradox and the aforementioned selection bias.

A work point count system coupled with back-propagation for solving double dummy bridge problem

The game ‘contract bridge’ is one of the most widely known card games comprising many fascinating aspects, such as bidding, playing and winning the trick including estimation of hand strength, the additional input data based on the human knowledge of the game to improve the quality of results. The game classified under a game of imperfect information is to be equally well-defined, since the decision made on any stage of the game is purely based on the decision that was made on the immediate preceding stage. The incompleteness of information, the real spirit of the card game in proceeding further deals of the game are taking into many forms especially during the distribution of cards for the next deal. One among the architectures of the Artificial Neural Network is considered by training on sample deals and used to estimate the number of tricks taken by one pair of bridge players is the key idea behind the Double Dummy Bridge Problem, implemented in this paper. The Cascade Correlation Neural Network architecture with supervised learning implemented to train data and hence to test it is coupled along with Work point count system.

A SOLUTION TO THE DOUBLE DUMMY CONTRACT BRIDGE PROBLEM INFLUENCED BY SUPERVISED LEARNING MODULE ADAPTED BY ARTIFICIAL NEURAL NETWORK

Contract Bridge is an intellectual game which motivates multiple skills and application of prior experience and knowledge, as no player knows accurately what moves other players are capable of making. The Bridge is a game played in the presence of imperfect information, yet its strategies must be well formulated, since the outcome at any intermediate stage is solely based on the choices made during the immediately preceding phase. In this paper, we train an Artificial Neural Network architecture using sample deals and use it to estimate the number of tricks to be taken by one pair of bridge players, which is the main challenge in the Double Dummy Bridge Problem. We focus on Back Propagation Neural Network Architecture with Back Propagation Algorithm with Sigmoidal transfer functions. We used two approaches namely, High - Card Point Count System and Distribution Point Method during the bidding phase of Contract Bridge. We experimented with two sigmoidal transfer functions namely, Log Sigmoid transfer function and the Hyperbolic Tangent Sigmoid function. Results reveal that the later performs better giving lower mean squared error on the output.

Assessing the Players’ Performance in the Game of Bridge: A Fuzzy Logic Approach

Contract bridge occupies nowadays a position of great prestige being, together with chess, the only mind games officially recognized by the International Olympic Committee. In the present paper an innovative method for assessing the total performance of bridge- players' belonging to groups of special interest(e.g. different bridge clubs during a tournament, men and women, new and old players, etc) is introduced, which is based on principles of fuzzy logic. For this, the cohorts under assessment are represented as fuzzy subsets of a set of linguistic labels characterizing their performance and the centroid defuzzification method is used to convert the fuzzy data collected from the game to a crisp number. This new method of assessment could be used informally as a complement of the official bridge-scoring methods for statistical and other obvious reasons. Two real applications related to simultaneous tournaments with pre-dealt boards, organized by the Hellenic Bridge Federation, are also presented, illustrating the importance of our results in practice.

Dopamine and risk choices in different domains: Findings among serious tournament bridge players

We explore how risk-taking in the card game contract bridge, and in a financial gamble, correlate with variation in the dopamine receptor D4 gene (DRD4) among serious tournament bridge players. In bridge risk-taking, we find significant interactions between genetic predisposition and skill. Among men with the 7-repeat allele of DRD4, namely 7R + men, those with more bridge skill take more good risks and fewer bad risks, while the opposite is found for less-expert 7R + men. Conversely, skill does not predict risk-taking among men without the 7R + allele. Consistent with some prior studies, we also find that 7R + men take more risk in the financial gamble. We find no relationship between 7R + and either risk measure among our female subjects. Our results suggest that the dopamine system plays an important role in individual differences in risk-taking among men, and is the first to distinguish between advantageous and disadvantageous risk-taking.

1.3.1 Increase Requirements Understanding by Playing Cooperative Games

AbstractSerious games are games whose primary purpose is not entertainment. Cooperative games structure communication (e.g. contract bridge) and cooperation (e.g. soccer) between players in the same group.Using serious, cooperative games improves Requirements Understanding (RU). This paper defines six RU games, maps them into ‘initial understanding space‘, and shows how to use a special Ouija board to choose the games to play on your project. An example of RU game selection is included.

The Cardturner: A Novel about a King, a Queen, and a Joker (review)

Reviewed by: The Cardturner: A Novel about a King, a Queen, and a Joker Deborah Stevenson, Editor Sachar, Louis. The Cardturner: A Novel about a King, a Queen, and a Joker. Delacorte, 2010. [352p]. Library ed. 978-0-385-90619-7 $20.99 Trade ed. ISBN 978-0-385-73662-6 $17.99 E-book ed. ISBN 978-0-375-89647-7 $17.99 Reviewed from galleys R Gr. 7-12. Summer was supposed to bring seventeen-year-old Alton Richards the usual hanging around, but instead he embarks on a strange enterprise when his great-uncle Lester, rendered blind by diabetes, asks Alton to serve as his cardturner in competitive contract bridge. Alton then finds himself enmeshed in a world of obsessive, intricate, and very smart gameplay, unraveling some misreported and painful family history, attracted to his great-uncle's previous cardturner, pretty Toni Castaneda, and, eventually, becoming the vessel of a bridge ambition that reaches supernaturally from beyond the grave. There is more bridge here than in all the rest of youth literature combined, but Sachar's amusing gimmick of providing an alert for the bridge-geeky passages (a whale, in a callback to Moby Dick's tendency to devolve into whaling trivia) and then briefly summarizing the plot-relevant extracts in following boxed text genuinely does permit readers to choose just how much bridge to immerse themselves in. Which may be all of it, since the book gives the game the tension of poker combined with the allure of code-cracking, and Alton's conversion to bridge junkie therefore makes perfect sense. The human drama is compelling as well; Alton's gruff, laconic great-uncle and his bridge cronies are a colorful assembly, while narrator Alton is a nice but unassertive guy who learns about the rewards of taking charge. The move to supernatural story is surprising but also intriguing, providing an unexpected route to resolution for past losses and current quandaries. Readers who like puzzles and those who appreciate all kinds of skilled gameplay will be drawn to this intricate, charmingly benign, yet cutthroat world. An afterword goes into even more detail, believe it or not, about bridge. Copyright © 2010 The Board of Trustees of the University of Illinois

Using dynamic programming to determine an optimal strategy in a contract bridge tournament

One form of contract bridge tournament comprises several rounds of matches in which players compete as pairs for ‘masterpoints’ awarded for each match won or drawn and for being highly placed at the end of the tournament. In the second and subsequent rounds, pairs are matched against other pairs that have been approximately equally successful so far. There has been vague discussion among bridge players of the possible advantages of ‘throwing’, that is, deliberately losing a match in round r so as to obtain a lower ranking and face an easier opponent in round r+1. This paper uses dynamic programming and data from one tournament to identify an optimal strategy (either ‘throw’ or ‘play to win’). The optimal strategy is a function of a pair's ability, its placing after each round, the relative rewards for winning a match and finishing high, the opponent's skill, and the round. For example, we find that a very weak pair should ‘throw’ and ‘play to win’ in alternate rounds.