Use of psychophysiological measures and interactive environments for understanding and training warfighter cross-cultural decision making

2012 ◽  
pp. 255-262
Keyword(s):  
Decision Making ◽  
Cross Cultural ◽  
Interactive Environments ◽  
Psychophysiological Measures ◽  
And Training

KEATS: A System to Support Knowledge Engineering and Training for Decision-Making Skills

1989 ◽  
Author(s):  
Fritz H. Brecke ◽  
Patrick Hays ◽  
Donald Johnston ◽  
Gail Slemon ◽  
Jane McGarvey ◽  
...  
Keyword(s):  
Decision Making ◽  
Knowledge Engineering ◽  
And Training

Making the most of individual differences in joint decisions

2018 ◽  
Author(s):  
Bahador Bahrami
Keyword(s):  
Decision Making ◽  
Direct Evidence ◽  
Cross Cultural ◽  
Collective Decision Making ◽  
Wisdom Of Crowds ◽  
Trade Off ◽  
Adaptive Value ◽  
Joint Decisions ◽  
Cultural Data ◽  
Better Than

Evidence for and against the idea that “two heads are better than one” is abundant. This chapter considers the contextual conditions and social norms that predict madness or wisdom of crowds to identify the adaptive value of collective decision-making beyond increased accuracy. Similarity of competence among members of a collective impacts collective accuracy, but interacting individuals often seem to operate under the assumption that they are equally competent even when direct evidence suggest the opposite and dyadic performance suffers. Cross-cultural data from Iran, China, and Denmark support this assumption of similarity (i.e., equality bias) as a sensible heuristic that works most of the time and simplifies social interaction. Crowds often trade off accuracy for other collective benefits such as diffusion of responsibility and reduction of regret. Consequently, two heads are sometimes better than one, but no-one holds the collective accountable, not even for the most disastrous of outcomes.

Research on sports aided teaching and training decision system oriented to deep convolutional neural network

2021 ◽  
pp. 1-15
Author(s):  
Qinyu Mei ◽  
Ming Li
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Control System ◽  
Convolutional Neural Network ◽  
Force Control ◽  
Control Experiment ◽  
Deep Convolutional Neural Network ◽  
Flexible Cable ◽  
Cable Force ◽  
And Training

Aiming at the construction of the decision-making system for sports-assisted teaching and training, this article first gives a deep convolutional neural network model for sports-assisted teaching and training decision-making. Subsequently, In order to meet the needs of athletes to assist in physical exercise, a squat training robot is built using a self-developed modular flexible cable drive unit, and its control system is designed to assist athletes in squatting training in sports. First, the human squat training mechanism is analyzed, and the overall structure of the robot is determined; second, the robot force servo control strategy is designed, including the flexible cable traction force planning link, the lateral force compensation link and the establishment of a single flexible cable passive force controller; In order to verify the effect of robot training, a single flexible cable force control experiment and a man-machine squat training experiment were carried out. In the single flexible cable force control experiment, the suppression effect of excess force reached more than 50%. In the squat experiment under 200 N, the standard deviation of the system loading force is 7.52 N, and the dynamic accuracy is above 90.2%. Experimental results show that the robot has a reasonable configuration, small footprint, stable control system, high loading accuracy, and can assist in squat training in physical education.

Naturalistic Decision Making in High Performance Team Sport Coaching

2015 ◽  
Vol 2 (2) ◽  
pp. 152-168 ◽  
Author(s):  
Stephen Harvey ◽  
John William Baird Lyle ◽  
Bob Muir
Keyword(s):  
Decision Making ◽  
High Performance ◽  
Recent Literature ◽  
Critical Factors ◽  
Naturalistic Decision Making ◽  
Problem Framing ◽  
Stimulated Recall ◽  
Suitable Framework ◽  
And Training

A defining element of coaching expertise is characterised by the coach’s ability to make decisions. Recent literature has explored the potential of Naturalistic Decision Making (NDM) as a useful framework for research into coaches’ in situ decision making behaviour. The purpose of this paper was to investigate whether the NDM paradigm offered a valid mechanism for exploring three high performance coaches’ decision-making behaviour in competition and training settings. The approach comprised three phases: 1) existing literature was synthesised to develop a conceptual framework of decision-making cues to guide and shape the exploration of empirical data; 2) data were generated from stimulated recall procedures to populate the framework; 3) existing theory was combined with empirical evidence to generate a set of concepts that offer explanations for the coaches’ decision-making behaviour. Findings revealed that NDM offered a suitable framework to apply to coaches’ decision-making behaviour. This behaviour was guided by the emergence of a slow, interactive script that evolves through a process of pattern recognition and/or problem framing. This revealed ‘key attractors’ that formed the initial catalyst and the potential necessity for the coach to make a decision through the breaching of a ‘threshold’. These were the critical factors for coaches’ interventions.

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