Online Chess Research Articles

Call it a Day: History Dependent Stopping Behavior

In this paper, we provide evidence of history-dependent stopping behavior. Using data from an online chess platform, we estimate a dynamic discrete choice model in which an agent may have time non-separable preferences over the stochastic outcomes of their actions. We show that the agent’s decisions cannot be reconciled in a model with time separable preferences and that there is substantial heterogeneity in preferences across players. In particular, there are two types of people: those who get discouraged by a loss and stop, and others, who get encouraged by failure and keep playing until a win. We show how to leverage the information about an agent’s type in market design to achieve various welfare goals. A counterfactual analysis demonstrates that a matching algorithm that incorporates stopping behavior can significantly increase the length of play.

Two Player Online Brain-Controlled Chess.

Brain-computer interfaces (BCIs) allow for translating brain signals into control commands, e.g. to control games. One of the biggest quests of the BCI community is to realize new exciting applications. In this paper, we present a two player online chess application where both players control their pieces solely with their brain activity. Control is realized in a two-step process where players first select the desired chess piece and then the field they want to move it to. A selection is accomplished with visual event-related potentials that are elicited by highlighting each possible piece or field one by one. Six healthy volunteers participated in our study by playing a game against each other in pairs over a free chess server. They successfully completed at least one match per pair. Our results show that even BCI-naive players obtain almost perfect control over the application. On average, 96% of the moves were correct. Most of the errors came from technical problems that can be corrected in future versions of the application. Given the high popularity of chess, this intuitive BCI game is an appealing new application for patients and for healthy users that want to explore BCIs.

Bias in the ELO-System of Online Chess

ELO is the key performance indicator in chess, a global and worldwide measure of chess skills and strength of chess play. Since their invention, ELO-systems are intended to be comparable and unbiased, so that chess players can know their level of play and can compare it among systems and internationally. Moreover, ELO is the defining feature of grandmasters with legal implications. Thus, it is highly important to only have unbiased ELO-system, whenever a terminology bearing ELO is used. However, most recent online chess sites seem to utilize a highly biased ELO-system that can maybe not be compared to tournament or FIDE chess ELO-score systems. It could be that online ELO-systems are strategically biased to make all hobby players around the world appear less professional by systemically down-shifting the ELO-score system. This short report offers some insights about this potential ELO-deflation phenomenon in online chess. It can be shown that online ELO-systems do not reflect real chess skill strength in ELO as measured by different methods: (1) game strength does not reflect tactical or strategic strength, (2) there is a shift in ELO-distribution between hundreds and up to thousand ELO-points of the average level player, e.g. FIDE RBB versus an online site, and (3) Elometer, a scientifically approved and scientifically standardized method also reveals this dramatic discrepancy and ELO-reduction. The reason for this deprivation of ELO-points seems to be an artificial ELO-scarcity that is introduced into the system whenever a new player enters the site and has to start with fewer ELOpoints than his or her skill level. There are not enough aggregated ELO-points that could mirror the sum of all chess skills in online chess and year after years it seems to worsen, while FIDE-ratings are rising slightly. Hence, this work reminds that the total ELO-points per rating system must be always adjusted, and there could be a strategic bias to downgrade all chess players. Millions of chess-players world-wide might be extremely underrated and their chess skills seem to be wrongly assessed and viewed.

Time to decide: Diurnal variations on the speed and quality of human decisions

Human behavior and physiology exhibit diurnal fluctuations. These rhythms are entrained by light and social cues, with vast individual differences in the phase of entrainment - referred as an individual’s chronotype - ranging in a continuum between early larks and late owls. Understanding whether decision-making in real-life situations depends on the relation between time of the day and an individual’s diurnal preferences has both practical and theoretical implications. However, answering this question has remained elusive because of the difficulty of measuring precisely the quality of a decision in real-life scenarios. Here we investigate diurnal variations in decision-making as a function of an individual’s chronotype capitalizing on a vast repository of human decisions: online chess servers. In a chess game, every player has to make around 40 decisions using a finite time budget and both the time and quality of each decision can be accurately determined. We found reliable diurnal rhythms in activity and decision-making policy. During the morning, players adopt a prevention focus policy (slower and more accurate decisions) which is later modified to a promotion focus (faster but less accurate decisions), without daily changes in performance.

망각곡선과 대결 기반 순위 결정 시스템을 적용한 영어 단어 학습 어플리케이션 개발

This paper presents English vocabulary memorization system using forgetting curve to automatically adjust the vocabulary difficulty to match learner`s level. Our system will decide the appropriate repetition cycle, depending on the number of memorizing words through the forgetting curve, then requires an iterative learning. No matter what learners know or do not know, words are reviewed. To save time by reviewing some words which have the highest probability that learners forget. And it provides vocabulary based on learner level, which makes learner maintain their interest and achievement. A general system provides vocabularies which difficulty matches with evaluated ones, or randomly provides some vocabularies without consideration of users` level. But we apply the Glicko system which is being used in the online chess game ranking system to adjust the vocabulary`s difficulty. We utilize the system used in the one-by-one player system to our vocabulary-human system. As a result, learners`s level and the vocabularies`s difficulty is measured in the review process. Moreover it maximizes the performance of English vocabulary memorization by applying feedbacks from practice testing and distributed learning.

Development of Embedded CAPTCHA Elements for Bot Prevention in Fischer Random Chess

Cheating in chess can take many forms and has existed almost as long as the game itself. The advent of computers has introduced a new form of cheating into the game. Thanks to the computational power of modern-day computers, a player can use a program to calculate thousands of moves for him or her, and determine the best possible scenario for each move and countermove. These programs are often referred to as “bots,” and can even play the game without any user interaction. In this paper, we describe a methodology aimed at preventing bots from participating in online chess games. The proposed approach is based on the integration of a CAPTCHA protocol into a game scenario, and the subsequent inability of bots to accurately track the game states. This is achieved by rotating the images of the individual chess pieces and adjusting their resolution in an attempt to render them unreadable by a bot. Feedback from users during testing shows that there is minimal impact on their ability to play the game. Players rated the difficulty of reading the pieces on a scale of one to ten, with an average rank of 6.5. However, the average number of moves to adjust to the distorted pieces was only 3.75. This tells us that, although it is difficult to read the pieces at first, it is easy to adjust quickly to the new image.

The effects of time pressure on chess skill: an investigation into fast and slow processes underlying expert performance

The ability to play chess is generally assumed to depend on two types of processes: slow processes such as search, and fast processes such as pattern recognition. It has been argued that an increase in time pressure during a game selectively hinders the ability to engage in slow processes. Here we study the effect of time pressure on expert chess performance in order to test the hypothesis that compared to weak players, strong players depend relatively heavily on fast processes. In the first study we examine the performance of players of various strengths at an online chess server, for games played under different time controls. In a second study we examine the effect of time controls on performance in world championship matches. Both studies consistently show that skill differences between players become less predictive of the game outcome as the time controls are tightened. This result indicates that slow processes are at least as important for strong players as they are for weak players. Our findings pose a challenge for current theorizing in the field of expertise and chess.

A security analysis of the Internet Chess Club

The Internet Chess Club (ICC) is a popular online chess server that started its existence in the early 1990s as the Internet chess server. Although the ICC Web site assures its users that the security protocol employed between the client and the server protects sensitive information, the authors show that this isn't true. This article examines two security aspects of the ICC. In moving from a free service to a commercial one, ICC's administrators introduced several enhancements to the original system, including time-stamping, a network security protocol, and online payments.