Simulation study of a decision-making model of squash competition, phase one: The analysis of the protocol

This study aims at specifying some of the cognitive processes underlying decision-making in squash competition. More specifically, the study focuses on the strategy of the defending player (D) when chosing among three categories of preparation (total preparation for one particular event, partial preparation in favor of one event and absence of biased preparation). D is viewed as an information processing system (IPS) placed in a problem-solving situation, the problem being what decision to reach. The results obtained in a preceding investigation about the nature of the information processed by a player to anticipate and prepare for the opponent's shot in a real game setting, are used to determine a typical protocol of the behavior of D. The analysis of this protocol allows one to formally define (in Backus-Normal-Form) the problem space of D which is also D's internal representation of the task environment. From the problem space are derived (1) the problem behavior graph depicting the search of D through his problem space for a solution, and (2) the production system (a set of conditional statements, each expressing what to do under specific conditions) defining the logic of the search. The results of this first phase of the simulation study of a decision-making model of squash competition show that the cognitive strategy of D is based upon the use of a specific preformed algorithm. This algorithm could be stored in some long-term memory and activated by the current state of information in short-term memory. Finally, the proposed model also leads to the suggestion that the cognitive strategy of the performer may be influenced by a variety of factors such as the experience of the player, the time pressure, the expectancies, the performer's confidence in his predictions and the mistakes caused by incorrect predictions.     

Response selection and execution skills of professionals and novices during singles tennis competition.

This study extended research on sport expertise concerning the development of cognitive and motor skills in singles tennis (McPherson, 1999). 12 adult male professional and novice tennis players were videotaped during singles competition. Opponents for matches were randomly selected within each group of participants. Two tennis experts utilized an observational scale to judge players' performance generated during competition for serves and shots following the serve, e.g.. return of serves, lobs. Each player was scored on three performance components: quality of movement to or control of the ball for serves or shots attempted (control skills), appropriateness of serve or shot selections in the context of game situations (response selection skills), and quality of serves or shots produced (response execution skills). Relative frequency scores for the highest category of each performance component were derived according to the number of opportunities to respond. Serve performance indicated both groups were able to control their serves: however, professionals made more tactical selections and forceful executions. Shot performance indicated professionals made more successful movement to and control of shots, tactical shot selections, and forcing shot executions than novices. Overall, players' tactical response selections were greater than their forceful response executions. Thus, assessing players' decisions during competition may provide vital information concerning tactical skill development. Further, professional players exhibited higher and more consistent tactical behavior than elite collegiate players examined in 1999 by McPherson. Findings were attributed to tactical knowledge and motor skill development resulting from competition and practice experiences.     

On fairness and learning agents in a bargaining model with uncertainty

The emergence of fair divisions in a repeated bargaining game is investigated in a computational model. Individuals of human societies often appeal to some norm of fairness in situations where an agreement over the division of a surplus is required. The employed framework consists of players alternating offers that describe possible ways to share a certain commodity. The players are allowed a limited number of offers to reach an agreement; if they fail to agree, the player who made the first offer, the lucky player, wins the whole lot at stake. Uncertainty is introduced in the process by randomly choosing the lucky player at the beginning of each iteration. In the experiments, the players acquired strategies by employing a variant of Q-learning, a reinforcement learning algorithm. Experiments were performed with different configurations of utility functions on the players’ preferences in taking actions in risky situations. Analysis of the results shows that the game theoretical model of a single shot of the bargaining game used in the experiments closely matches the outcomes obtained in the simulated framework, despite the differences in the quality of the players, who are assumed to be fully rational in the theoretical model. Learning agents that are timid toward risky situations manage to acquire strategies that lead to fair outcomes when playing against each other, but find themselves in a disadvantageous position when confronting bolder types.     

The hot hand exists in volleyball and is used for allocation decisions

The "hot hand" belief in sports refers to the conviction that a player has a higher chance of making a shot after two or three successful shots than after two or three misses (resulting in "streaks"). This belief is usually considered a cognitive fallacy, although it has been conjectured that in basketball the defense will attack a "hot" player and prevent streaks from occurring. To address this argument, we provide the first study on the hot hand in volleyball, where the net limits direct defensive counterstrategies, meaning that streaks can more likely emerge if a player is hot. We first establish that athletes believe in the hot hand in volleyball (Study 1A). Analyzing the top 26 first-division players, we then show that streaks do exist for half of the players (Study 1B). Coaches can detect players' performance variability and use it to make strategic decisions (Study 2A). Playmakers are also sensitive to streaks and rely on them when deciding to whom to allocate the ball (Study 2B). We conclude that for volleyball the hot hand exists, coaches and playmakers are able to detect it, and playmakers tend to use it "adaptively," which results in more hits for a team.     

A cognitive model of planning

This paper presents a cognitive model of the planning process. The model generalizes the theoretical architecture of the Hearsay-ll system. Thus, it assumes that planning comprises the activities of a variety of cognitive “specialists.” Each specialist can suggest certain kinds of decisions for incorporation into the plan in progress. These include decisions about: (a) how to approach the planning problem; (b) what knowledge bears on the problem; (c) what kinds of actions to try to plan; (d) what specific actions to plan; and (e) how to allocate cognitive resources during planning. Within each of these categories, different specialists suggest decisions at different levels of abstraction. The activities of the various specialists are not coordinated in any systematic way. Instead, the specialists operate opportunistically, suggesting decisions whenever promising opportunities arise. The paper presents a detailed account of the model and illustrates its assumptions with a “thinking aloud” protocol. It also describes the performance of a computer simulation of the model. The paper contrasts the proposed model with successive refinement models and attempts to resolve apparent differences between the two points of view.     

Scheduling and programming of rapid finger sequences: tests and elaborations of the hierarchical editor model

Is a response sequence executed only after the sequence has been fully programmed, as discrete processing models predict, or does execution begin before programming has been completed, as continuous processing models predict? To address this issue, we tested a discrete processing model of human motor performance, the hierarchical editor model of Rosenbaum, Inhoff, and Gordon (1984). This model was developed to account for data from experiments in which people perform one of two possible finger sequences, depending on the identity of a choice signal. The model assumes a hierarchically organized motor program that is first "edited" to resolve any uncertainties and is then "executed" to produce the desired responses. Three experiments reported here show that, contrary to the model's predictions and some well-known motor programming results (Sternberg, Monsell, Knoll, & Wright, 1978), the reaction time to begin a response sequence actually decreases with the length of the sequence under some choice conditions. We account for these results with a model that allows execution to begin while editing is still in progress. A key assumption in the model is that subjects schedule execution so that means and variances of interresponse times are minimized.     

How race affects evidence accumulation during the decision to shoot

The biasing role of stereotypes is a central theme in social cognition research. For example, to understand the role of race in police officers’ decisions to shoot, participants have been shown images of Black and White males and instructed to shoot only if the target is holding a gun. Findings show that Black targets are shot more frequently and more quickly than Whites. The decision to shoot has typically been modeled and understood as a signal detection process in which a sample of information is compared against a criterion, with the criterion set for Black targets being lower. We take a different approach, modeling the decision to shoot as a dynamic process in which evidence is accumulated over time until a threshold is reached. The model accounts for both the choice and response time data for both correct and incorrect decisions using a single set of parameters. Across four studies, this dynamic perspective revealed that the target’s race did not create an initial bias to shoot Black targets. Instead, race impacted the rate of evidence accumulation with evidence accumulating faster to shoot for Black targets. Some participants also tended to be more cautious with Black targets, setting higher decision thresholds. Besides providing a more cohesive and richer account of the decision to shoot or not, the dynamic model suggests interventions that may address the use of race information in decisions to shoot and a means to measure their effectiveness.     

A hybrid model using neural networks and ACT-R

How do people make decisions given contradictory information? This paper presents a model of how expert DSOs (defensive system operators) on a B1 bomber examine a complex series of signals, categorize whether those signals are dangerous or not, and then make a decision on the basis of those signals. This decision is made more difficult because an automatic on-board computer sometimes identifies the signal incorrectly. Therefore, the DSO must compare the actual signal to the system ID “guess.” The proposed model is a hybrid model, combining a standard neural network and ACT-R, a production system, which achieves a high degree of success.     

Basketball players minimize the effect of motor noise by using near-minimum release speed in free-throw shooting

The aim of this study was to clarify the strategy used by basketball players during free-throw shooting to improve performance in the presence of motor noise. Two possible hypotheses were examined: the players minimize the release speed to decrease signal-dependent noise or the players maximize the shot success probability by accounting for their variability. Eight collegiate players and one professional player participated in this study by attempting shots from the free-throw line using a motion capture system. The solution manifold consisting of ball parameters at release was calculated and the optimal strategy was simulated by considering ball parameter variability; this result was compared with the actual data. Our results showed that participants selected the solution of near-minimum release speed. The deviation of the measured release angle from the minimum-speed angle was close to zero (2.8 ± 3.1^∘). However, an increase in speed-dependent noise did not have a significant influence on the ball landing position through simulation. Additionally, the effect of release angle error on the ball landing position was minimum when using the minimum speed strategy. Therefore, the players minimize the release speed to minimize the effect of the release error on performance, instead of minimizing the speed-dependent noise itself. In other words, the strategy is “near-minimum-speed strategy” as well as “minimum-error-propagation strategy”. These findings will be important for understanding how sports experts deal with intrinsic noise to improve performance.     

Risk taking in achievement-oriented situations: Do people really maximize affect or competence information?

Several studies of choice behavior (risk taking) in achievement-oriented situations are reanalyzed. The usual ways of pooling all choices over trials and subjects conceal the series of subjects' decisions and the dynamics inherent in these decisions. A basic strategy of subjects in an achievement-oriented choice situation seems to be to start with an easy task, choose a more difficult one whenever you succeed, and stay mostly at the same difficulty level whenever you fail. A computer model, in which such simple assumptions are made, generates preference functions over the order of difficulty levels that are indistinguishable from those found in empirical studies. It is concluded that the study of choice behavior in achievement-oriented situations should be based on the analysis of the series of single decisions by one subject. For this we need models that allow the predictions of such decisions and the prediction of action-controlling cognitions and emotions.     

Conflict tasks and the diffusion framework: Insight in model constraints based on psychological laws

Formal models of decision-making have traditionally focused on simple, two-choice perceptual decisions. To date, one of the most influential account of this process is Ratcliff’s drift diffusion model (DDM). However, the extension of the model to more complex decisions is not straightforward. In particular, conflicting situations, such as the Eriksen, Stroop, or Simon tasks, require control mechanisms that shield the cognitive system against distracting information. We adopted a novel strategy to constrain response time (RT) models by concurrently investigating two well-known empirical laws in conflict tasks, both at experimental and modeling levels. The two laws, predicted by the DDM, describe the relationship between mean RT and (i) target intensity (Piéron’s law), (ii) standard deviation of RT (Wagenmakers–Brown’s law). Pioneering work has shown that Piéron’s law holds in the Stroop task, and has highlighted an additive relationship between target intensity and compatibility. We found similar results in both Eriksen and Simon tasks. Compatibility also violated Wagenmakers–Brown’s law in a very similar and particular fashion in the two tasks, suggesting a common model framework. To investigate the nature of this commonality, predictions of two recent extensions of the DDM that incorporate selective attention mechanisms were simulated and compared to the experimental results. Both models predict Piéron’s law and the violation of Wagenmakers–Brown’s law by compatibility. Fits of the models to the RT distributions and accuracy data allowed us to further reveal their relative strengths and deficiencies. Combining experimental and computational results, this study sets the groundwork for a unified model of decision-making in conflicting environments.     

The simplest complete model of choice response time: linear ballistic accumulation

We propose a linear ballistic accumulator (LBA) model of decision making and reaction time. The LBA is simpler than other models of choice response time, with independent accumulators that race towards a common response threshold. Activity in the accumulators increases in a linear and deterministic manner. The simplicity of the model allows complete analytic solutions for choices between any number of alternatives. These solutions (and freely-available computer code) make the model easy to apply to both binary and multiple choice situations. Using data from five previously published experiments, we demonstrate that the LBA model successfully accommodates empirical phenomena from binary and multiple choice tasks that have proven difficult for other theoretical accounts. Our results are encouraging in a field beset by the tradeoff between complexity and completeness.     

Integrating commons dilemma findings in a general dynamic model of cooperative behavior in resource crises

The research on commons dilemmas is characterized by innumerable published findings, each standing relatively isolated from the other. To date there is little integration of the findings under a unified concept. The present contribution aims to integrate already existing findings in a general dynamic model of cooperative behavior in resource crises by means of computer simulation. The model postulates that people base their decisions regarding resource use on both ecological and social information. Whether or not ecological or social information will dominate, however, depends on people's social values, attributions, and their perceptions of the state of the resource. The advantage of the simulation method used is that successful integration of the findings can be shown explicitly, as the simulation then replicates the experimental data. With the model presented here, it is also possible to let variables work together whose interaction has not yet been investigated in real experiments. For instance, the simulation model allows us to hypothesize that people, in dependency upon their resource uncertainty and in dependency upon their attributions, utilize a resource completely differently if the resource is in an optimal or sub‐optimal condition. Copyright © 2002 John Wiley & Sons, Ltd.     

Capturing and testing perceptual-cognitive expertise: A comparison of stationary and movement response methods

Numerous methods have been used to study expertise and performance. In the present article, we compare the cognitive thought processes of skilled soccer players when responding to film-based simulations of defensive situations involving two different experimental conditions. Participants either remained stationary in a seated position (n = 10) or were allowed to move (n = 10) in response to life-size film sequences of 11 versus 11 open-play soccer situations viewed from a player’s perspective. Response accuracy and retrospective verbal reports of thinking were collected across the two task conditions. In the movement-based response group, participants generated a greater number of verbal report statements, including a higher proportion of evaluation, prediction, and action planning statements, than did participants in the stationary group. Findings suggest that the processing strategies employed during performance differ depending on the nature of the response required of participants. Implications for behavioral methods and experimental design are discussed.     

Implicit motor learning and complex decision making in time-constrained environments

The cost-effectiveness of the implicit (procedural) knowledge that supports motor expertise enables surprisingly efficient performance when a decision and an action must occur in close temporal proximity. The authors argue that if novices learn the motor component of performance implicitly rather than explicitly, then they will also be efficient when they make a decision and execute an action in close temporal proximity. Participants (N = 35) learned a table tennis shot implicitly or explicitly. The authors assessed participants' motor performance and movement kinematics under conditions that required a concurrent low-complexity decision or a concurrent high-complexity decision about where to direct each shot. Performance was disrupted only for participants who learned explicitly when they made high-complexity decisions but not when they made low-complexity decisions. The authors conclude that implicit motor learning encourages cognitively efficient motor control more than does explicit motor learning, which allows performance to remain stable when time constraints call for a complex decision in tandem with a motor action.     

Defensive Pessimism,Anxiety, and the Complexity of Evaluating Self‐Regulation

Defensive pessimism is a motivated cognitive strategy that helps people manage their anxiety and pursue their goals. Individuals who use defensive pessimism set low expectations, and play through extensive mental simulations of possible outcomes as they prepare for goal‐relevant tasks and situations. Research on a variety of phenomena, from self‐handicapping to stereotype threat, demonstrates the potential effectiveness of defensive pessimism as a self‐regulation strategy. Review of this research provides an illustration of the complexity of self‐regulation efforts, because understanding how and why defensive pessimism works requires an integrated understanding the role of traits, motivations, and self structures within the individual, the resultant goals toward which strategies are directed, and the particular constraints of different situations and cultural contexts.     

Expert-novice differences in cognitive and execution skills during tennis competition

This study deals with decision and execution behavior of tennis players during competition. The study is based on the expert-novice paradigm and aims to identify differences between both groups in the decision-making and execution variables in serve and shot actions in tennis. Six expert players (elite Spanish tennis players) and six novice players (grade school tennis players) took part in this study. To carry out this study, the observation protocol defined by McPherson and Thomas in 1989, in which control, decision-making and execution variables were included, was used, where it was applied to the performance of the tennis player in a real match situation. In the analysis, significant differences between experts and novices in decision-making and execution variables are found wherein it can be observed that experts display a greater ability to make the appropriate decisions, selecting the most tactical responses to put pressure on the opponent. Expert tennis players were also able to carry out forceful executions to their opponent with greater efficiency, making the opponent's response to a large extent more difficult. These findings are in accordance with those of McPherson and colleagues.     

Nested Logit Models for Multiple-Choice Item Response Data

Nested logit item response models for multiple-choice data are presented. Relative to previous models, the new models are suggested to provide a better approximation to multiple-choice items where the application of a solution strategy precedes consideration of response options. In practice, the models also accommodate collapsibility across all distractor categories, making it easier to allow decisions about including distractor information to occur on an item-by-item or application-by-application basis without altering the statistical form of the correct response curves. Marginal maximum likelihood estimation algorithms for the models are presented along with simulation and real data analyses.     

Response bias in judging deceptive movements

Two not mutually exclusive explanations, perceptual and motor expertise, account for the finding that experts outperform novices in recognizing deceptive actions from bodily (kinematic) cues. The aim of the present study was twofold: First, we sought to examine the impact of motor and perceptual expertise on distinguishing deceptive and non-deceptive actions. Second, we tested the hypothesis that differences in perceptual judgments on deceptive movements vs. non-deceptive movements do not necessarily need to be caused by either perceptual or motor expertise differences, but can also be a result of response bias. Skilled handball players (field players and goalkeepers) and novices had to detect whether a penalty-taker shot or faked a shot at the goal. Signal detection theory (SDT) analysis revealed that skilled handball players outperformed novices in discriminating shots from fakes. No differences in perceptual sensitivity were found between the goalkeepers and the field players. However, SDT analysis showed that goalkeepers were significantly biased to judge movements as deceptive, while neither field players nor novices showed this response bias.     

Self-Determination, Wellbeing, and Threats of Harm

David Rodin argues that the right of national‐defence as conceived in international law cannot be grounded in the end of defending the lives of individuals. Firstly, having this end is not necessary because there is a right of defence against an invasion that threatens no lives. However, in this context we are to understand that ‘defending lives’ includes defending against certain non‐lethal threats. I will argue that threats to national‐self determination and self‐government are significant non‐lethal threats to the wellbeing of individuals that can justify lethal defensive force. Therefore the end of defending individuals can ground a right of national‐defence against a ‘bloodless invasion’. Secondly, Rodin argues that defending lives is not a sufficient condition for military action to be national self‐defence, because humanitarian intervention is military action to defend individuals, and such action is in deep tension with national self‐defence. I will argue that a reductive account, grounded in claims of need and threats of harm, can justify principles of both intervention and non‐intervention on the same grounds; that is, protecting the wellbeing of individuals.