Some Determinants of Multidimensional Points of View: Two Studies

1970 ◽  
Vol 31 (2) ◽  
pp. 659-670 ◽  
Author(s):  
Daniel Landis ◽  
Robert M. Slivka
Keyword(s):  
Decision Making ◽  
Extensive Study ◽  
Stepwise Multiple Regression ◽  
Perceptual Style ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Points Of View ◽  
Relationship Of ◽  
The Relationship ◽  
I 31

Two studies are reported bearing on the relationship of multidimensional points-of-view to cognitive perceptual style and complex decision-making performance. In Study I, 31 Ss scaled two sets of stimuli. Factor loadings from a points-of-view analysis were correlated with scores from 8 cognitive perceptual style measures. Sufficient significant correlations were found to warrant a more extensive study. In Study II, 120 Ss scaled 12 problem maps after solving the problems. Each S was also administered the measures used in Study I. The scaling data were subjected to a points-of-view analysis and related to the solution and style data by a stepwise multiple regression procedure. Results indicated that: (1) multidimensional points of view are related to style data; (2) points of view are also related to complex decision-making performance; and (3) some of the previously reported style groups break down into sub-groups.

Fear of Death in Medical Students 1998-2019

2021 ◽  
Vol 66 (Special Issue) ◽  
pp. 74-75
Author(s):  
Montserrat Esquerda ◽  
◽  
Ana Isabel Parra ◽  
Anna M. Agustí ◽  
Josep Pifarre ◽  
...  
Keyword(s):  
Decision Making ◽  
Medical Student ◽  
Medical Students ◽  
End Of Life ◽  
Ethical Decision Making ◽  
Fear Of Death ◽  
Daily Work ◽  
Complex Decision Making ◽  
Complex Decision ◽  
The Relationship

"Medical students are close in their daily work with the world of suffering and death, living with pain and loss, without having received in general any regulated preparation to face it. This lack of training is associated with a sociocultural context that avoids speaking or approaching death, making it difficult for the medical student and the professionals themselves to develop the concept of death, adequate coping strategies, talking about complex decision-making at the end of life, acceptance of limitations or more generally to palliative medicine. This fear of death can hinder ethical decision-making and end-of-life conversations. The aim of the study is to assess fear of death in a sample of medical students, from 1998 to 2019, the relationship between fear of death and age, gender, course, beliefs or experiences of death and assess the evolution of death during these 20 years. Method The study included 756 medical students, from the courses between 1998 and 2019, who were given Collet-Lester revised Scale of Fear of Death and a questionnaire of sociodemographic and biographical variables. Results The analysis of the variables surveyed indicates that medical students present an intermediate level of fear of death and the process of dying. Fear of death has increased in these decades; it also increases during medical courses. Conclusions With the results obtained, medical schools should include a more oriented a specific approach in death and suffering that allows the medical student to obtain greater knowledge and be trained in accompanying death and talking about death. "

Some Determinants of Certitude Judgments in a Complex Decision-Making Task

1969 ◽  
Vol 24 (2) ◽  
pp. 447-460 ◽  
Author(s):  
Daniel Landis ◽  
Robert M. Slivka ◽  
Carl A. Silver
Keyword(s):  
Experimental Situation ◽  
Complex Problem ◽  
Complex Problem Solving ◽  
Perceptual Style ◽  
Male College ◽  
Complex Decision Making ◽  
Complex Decision ◽  
The Relationship ◽  
Problem Data ◽  
Problem Solving Task

This research investigated the relationship between certitude and decision adequacy using a complex problem-solving task. 120 male college Ss, serving with pay, solved 12 problems which varied in amount of information and method of coding. Each S also estimated the adequacy of his solution as well as the affective tone of the situation after the solution of each problem. Data were also available from a set of cognitive-perceptual-style measures. Results indicated that: (1) the correlation between decision adequacy and certitude is low and probably of negligible significance; (2) certitude is closely related to affective aspects of the stimulus; and, (3) level of certitude is related to the level of cognitive and perceptual scanning employed by S. It is suggested that (1) the correlation between certitude and decision adequacy may also be a function of the extensiveness of the response repertoire permitted S in the experimental situation, and (2) more intensive examination of individual differences with respect to accuracy of certitude judgments may be necessary.

scholarly journals Goal-driven active learning

2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Nicolas Bougie ◽  
Ryutaro Ichise
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Learning Process ◽  
Real World ◽  
Imitation Learning ◽  
Learning Approaches ◽  
Wide Range ◽  
Fixed Set ◽  
Complex Decision Making ◽  
Complex Decision

AbstractDeep reinforcement learning methods have achieved significant successes in complex decision-making problems. In fact, they traditionally rely on well-designed extrinsic rewards, which limits their applicability to many real-world tasks where rewards are naturally sparse. While cloning behaviors provided by an expert is a promising approach to the exploration problem, learning from a fixed set of demonstrations may be impracticable due to lack of state coverage or distribution mismatch—when the learner’s goal deviates from the demonstrated behaviors. Besides, we are interested in learning how to reach a wide range of goals from the same set of demonstrations. In this work we propose a novel goal-conditioned method that leverages very small sets of goal-driven demonstrations to massively accelerate the learning process. Crucially, we introduce the concept of active goal-driven demonstrations to query the demonstrator only in hard-to-learn and uncertain regions of the state space. We further present a strategy for prioritizing sampling of goals where the disagreement between the expert and the policy is maximized. We evaluate our method on a variety of benchmark environments from the Mujoco domain. Experimental results show that our method outperforms prior imitation learning approaches in most of the tasks in terms of exploration efficiency and average scores.

Sign in / Sign up

Export Citation Format

Share Document