Judgement and Decision Making in Dynamic Tasks

Abstract : This research note presents a theory of task conditions on the grounds that such a theory is a prerequisite for studying dynamic decision making. The principal features of the theory are: a) a task-cognition inducement principle, b) a distinction drawn between surface and depth characteristics of tasks, and c) a task continuum index. Also presented is a theory of cognition in dynamic tasks, the main features of which are a cognitive continuum index set in parallel with the continuum index, and a description of the role of pattern seeking and functional-relation seeking in dynamic tasks. The practical consequences for both designers and operators are indicated.

[1]  R. Dawes,et al.  Heuristics and Biases: Clinical versus Actuarial Judgment , 2002 .

[2]  G. Vining,et al.  Data Analysis: A Model-Comparison Approach , 1989 .

[3]  J J Tribbia,et al.  Scientific basis of modern weather prediction. , 1987, Science.

[4]  Berndt Brehmer.  Systems Design and the Psychology of Complex Systems , 1987 .

[5]  K. R. Hammond,et al.  Generalizing over conditions by combining the multitrait-multimethod matrix and the representative design of experiments. , 1986, Psychological bulletin.

[6]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[7]  R. Hogarth,et al.  Judging probable cause. , 1986 .

[8]  V. De Keyser,et al.  Expert logic v. operator logic , 1985 .

[9]  Jens Rasmussen,et al.  The role of hierarchical knowledge representation in decisionmaking and system management , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  A. Tversky,et al.  Weighting common and distinctive features in perceptual and conceptual judgments , 1984, Cognitive Psychology.

[11]  G. Pitz,et al.  Judgment and decision: theory and application. , 1984, Annual review of psychology.

[12]  Jens Rasmussen,et al.  Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[13]  William B. Rouse,et al.  Models of human problem solving: Detection, diagnosis, and compensation for system failures , 1982, Autom..

[14]  Thomas S. Kuhn,et al.  SCIENTIFIC REVOLUTIONS , 1982, Pediatrics.

[15]  A. Tversky,et al.  Similarity, separability, and the triangle inequality. , 1982, Psychological review.

[16]  Nancy Pennington,et al.  Juror decision-making models: The generalization gap. , 1981 .

[17]  N. Pennington,et al.  Human judgment and decision making: Theories, methods, and procedures , 1980 .

[18]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[19]  R. Dawes,et al.  Linear models in decision making. , 1974 .

[20]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[21]  A. H. Murphy,et al.  forecasters and probability forecasts: some current problems1,2 , 1971 .

[22]  L. Tucker.  A SUGGESTED ALTERNATIVE FORMULATION IN THE DEVELOPMENTS BY HURSCH, HAMMOND, AND HURSCH, AND BY HAMMOND, HURSCH, AND TODD. , 1964, Psychological review.

[23]  H. Chestnut.  International Federation of Automatic Control , 2013, Nature.

[24]  E. Brunswik.  Perception and the Representative Design of Psychological Experiments , 1957 .