The classic notion of a win–win situation has a key flaw in that it cannot always offer the parties equal amounts of winningsbecause each party believes they are winners. In reality, one party may ...win more than the other. This strategy is not limited to a single product or negotiation; it may be applied to a variety of situations in life. We present a novel way to measure the win–win situation in this paper. The proposed method employs fuzzy logic to create a mathematical model that aids negotiators in quantifying their winning percentages. The model is put to the test on real-life negotiation scenarios such as the Iraqi–Jordanian oil deal and iron ore negotiation (2005–2009), in addition to scenarios from the game of chess. The presented model has proven to be a useful tool in practice and can be easily generalized to be utilized in other domains as well.
It has been proposed that playing chess enables children to improve their ability in mathematics. These claims have been recently evaluated in a meta-analysis (Sala & Gobet,
2016
,
Educational ...Research Review, 18,
46–57), which indicated a significant effect in favor of the groups playing chess. However, the meta-analysis also showed that most of the reviewed studies used a poor experimental design (in particular, they lacked an active control group). We ran two experiments that used a three-group design including both an active and a passive control group, with a focus on mathematical ability. In the first experiment (
N
= 233), a group of third and fourth graders was taught chess for 25 hours and tested on mathematical problem-solving tasks. Participants also filled in a questionnaire assessing their meta-cognitive ability for mathematics problems. The group playing chess was compared to an active control group (playing checkers) and a passive control group. The three groups showed no statistically significant difference in mathematical problem-solving or metacognitive abilities in the posttest. The second experiment (
N
= 52) broadly used the same design, but the Oriental game of Go replaced checkers in the active control group. While the chess-treated group and the passive control group slightly outperformed the active control group with mathematical problem solving, the differences were not statistically significant. No differences were found with respect to metacognitive ability. These results suggest that the effects (if any) of chess instruction, when rigorously tested, are modest and that such interventions should not replace the traditional curriculum in mathematics.
Imperfect information games have served as benchmarks and milestones in fields of artificial intelligence (AI) and game theory for decades. Sensing and exploiting information to effectively describe ...the game environment is of critical importance for game solving, besides computing or approximating an optimal strategy. Reconnaissance blind chess (RBC), a new variant of chess, is a quintessential game of imperfect information where the player’s actions are definitely unobserved by the opponent. This characteristic of RBC exponentially expands the scale of the information set and extremely invokes uncertainty of the game environment. In this paper, we introduce a novel sense method, Heuristic Search of Uncertainty Control (HSUC), to significantly reduce the uncertainty of real-time information set. The key idea of HSUC is to consider the whole uncertainty of the environment rather than predicting the opponents’ strategy. Furthermore, we realize a practical framework for RBC game that incorporates our HSUC method with Monte Carlo Tree Search (MCTS). In the experiments, HSUC has shown better effectiveness and robustness than comparison opponents in information sensing. It is worth mentioning that our RBC game agent has won the first place in terms of uncertainty management in NeurIPS 2019 RBC tournament.
This article focuses on the recent advances in the field of reinforcement learning (RL) as well as the present state–of–the–art applications in games. First, we give a general panorama of RL while at ...the same time we underline the way that it has progressed to the current degree of application. Moreover, we conduct a keyword analysis of the literature on deep learning (DL) and reinforcement learning in order to analyze to what extent the scientific study is based on games such as ATARI, Chess, and Go. Finally, we explored a range of public data to create a unified framework and trends for the present and future of this sector (RL in games). Our work led us to conclude that deep RL accounted for roughly 25.1% of the DL literature, and a sizable amount of this literature focuses on RL applications in the game domain, indicating the road for newer and more sophisticated algorithms capable of outperforming human performance.
To explore the perceptual component of chess expertise, we monitored the eye movements of expert and novice chess players during a chess-related visual search task that tested anecdotal reports that ...a key differentiator of chess skill is the ability to visualize the complex moves of the knight piece. Specifically, chess players viewed an array of four minimized chessboards, and they rapidly searched for the target board that allowed a knight piece to reach a target square in three moves. On each trial, there was only one target board (i.e., the "Yes" board), and for the remaining "lure" boards, the knight's path was blocked on either the first move (the "Easy No" board) or the second move (i.e., "the Difficult No" board). As evidence that chess experts can rapidly differentiate complex chess-related visual patterns, the experts (but not the novices) showed longer first-fixation durations on the "Yes" board relative to the "Difficult No" board. Moreover, as hypothesized, the task strongly differentiated chess skill: Reaction times were more than four times faster for the experts relative to novices, and reaction times were correlated with within-group measures of expertise (i.e., official chess ratings, number of hours of practice). These results indicate that a key component of chess expertise is the ability to rapidly recognize complex visual patterns.
The study replicated research on metacontingencies that used a chessboard simulating a simplified chess game, in a completely online environment, with participants in their homes. Dyads of ...participants had to work together moving two knights in L-shape. Each trial ended when the knights met in adjacent squares. The squares where the knights should meet (aggregate product AP) varied in two conditions, using an ABAB design. In conditions A, knights should meet anywhere on the chessboard, and there was no consequence. In conditions B, the matrix of reinforceable squares was gradually reduced in four phases and knights’ encounters were followed by different messages when correct or incorrect (cultural consequences). In group 1, five dyads were allowed to communicate. In group 2, dyads had no access to video call. Results of group 1 corroborate the findings of the original studies that showed a decrease in APs variability from conditions A to B, when communication was allowed. Group 2 showed similar results, therefore extending to the setting that not allowed communication. The online platform XadrezWeb, developed for this study, was an important tool to program the interlocked behavior contingencies and collect data during social isolation.
In the last few years, information security based on chaotic systems has become increasingly important. This paper proposes a new encryption algorithm by merging a hyper-chaotic system and a famous ...game, to inject more robustness and information security against attacks. This proposed new cryptosystem is divided into two main random parts: a confusion which is an XOR between an image and a mask created by a 5-D hyper-chaotic system equation. Diffusion is a new permutation technique involving the application of chess moves combined with a hyper-chaotic 5-D system. The algorithm comprises six rounds the number of game pieces, whose cipher image is obtained after a combination of confusion and diffusion applied to the clear image. Experimental and analytical results show that the proposed algorithm demonstrates lossless encryption and decryption, with security tests confirming the good encryption results of our work, a larger key space, with a key size of 2
250
. Numerical simulation demonstrates that the proposed system is safe and reliable for image encryption.
Endgame databases can be difficult to use in tree search when database sizes remain large even after compression. Given the same endgame, we discover that the compression ratios vary significantly ...when using different encoding schemes. The intuition is that when a set of positions mapped into a continuous chunk of segments have similar values, block-based compression libraries such as zlib can yield a better compression ratio than cases where segments contain diversified values. However, finding the optimal encoding scheme by exhaustive enumeration is time-infeasible for endgame databases with a large number of pieces. We propose a novel approach using deep learning to obtain an encoding scheme so that the compression ratio is suitable for practical purposes. Our approach can be applied to chess-like games.
In this paper we report the existence of long-range memory in the opening moves of a chronologically ordered set of chess games using an extensive chess database. We used two mapping rules to build ...discrete time series and analyzed them using two methods for detecting long-range correlations; rescaled range analysis and detrended fluctuation analysis. We found that long-range memory is related to the level of the players. When the database is filtered according to player levels we found differences in the persistence of the different subsets. For high level players, correlations are stronger at long time scales; whereas in intermediate and low level players they reach the maximum value at shorter time scales. This can be interpreted as a signature of the different strategies used by players with different levels of expertise. These results are robust against the assignation rules and the method employed in the analysis of the time series.
•We introduced two mapping rules for building discrete time series from a set of chess games.•We found long range correlations in an extensive chess database.•The extent of long range correlations depends on the level of the players.•Depending on the level of expertise the players use different strategies.
Playing Chess with HIV Ward, Andrew B.
Immunity (Cambridge, Mass.),
02/2019, Volume:
50, Issue:
2
Journal Article
Peer reviewed
Open access
HIV envelope glycoprotein (Env) exhibits extreme antigenic variation that can be countered by an amazing class of immunoglobulins known as broadly neutralizing antibodies. Dingens et al. (2019) use ...saturating mutagenesis of Env to play out all of the potential bnAb escape strategies and in doing so define the functional epitopes of these important vaccine and immunotherapeutic targets.
HIV envelope glycoprotein (Env) exhibits extreme antigenic variation that can be countered by an amazing class of immunoglobulins known as broadly neutralizing antibodies. Dingens et al. (2019) use saturating mutagenesis of Env to play out all of the potential bnAb escape strategies and in doing so define the functional epitopes of these important vaccine and immunotherapeutic targets.
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