A New Proposal for Fuzzy Rough Approximations and Gradual Decision Rule Representation

2004 ◽  
pp. 319-342 ◽  
Author(s):  
Salvatore Greco ◽  
Masahiro Inuiguchi ◽  
Roman Słowiński
Keyword(s):  
Decision Rule ◽  
Rule Representation

Decay of Response Rule Representation during Task Switching

2011 ◽  
Author(s):  
Jonathan G. Hakun ◽  
Susan M. Ravizza
Keyword(s):  
Task Switching ◽  
Response Rule ◽  
Rule Representation

The Role of a Decision Rule in Symptomatic Pulmonary Embolism Patients with a Non-high Probability Ventilation-perfusion Scan

1997 ◽  
Vol 78 (02) ◽  
pp. 794-798 ◽  
Author(s):  
Bowine C Michel ◽  
Philomeen M M Kuijer ◽  
Joseph McDonnell ◽  
Edwin J R van Beek ◽  
Frans F H Rutten ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Decision Rule ◽  
Predictive Value ◽  
Patient Population ◽  
High Probability ◽  
Characteristic Curve ◽  
Stepwise Logistic Regression ◽  
Pulmonary Angiogram ◽  
Symptomatic Pulmonary Embolism ◽  
Perfusion Scan

Summary Background: In order to improve the use of information contained in the medical history and physical examination in patients with suspected pulmonary embolism and a non-high probability ventilation-perfusion scan, we assessed whether a simple, quantitative decision rule could be derived for the diagnosis or exclusion of pulmonary embolism. Methods: In 140 consecutive symptomatic patients with a non- high probability ventilation-perfusion scan and an interpretable pulmonary angiogram, various clinical and lung scan items were collected prospectively and analyzed by multivariate stepwise logistic regression analysis to identify the most informative combination of items. Results: The prevalence of proven pulmonary embolism in the patient population was 27.1%. A decision rule containing the presence of wheezing, previous deep venous thrombosis, recently developed or worsened cough, body temperature above 37° C and multiple defects on the perfusion scan was constructed. For the rule the area under the Receiver Operating Characteristic curve was larger than that of the prior probability of pulmonary embolism as assessed by the physician at presentation (0.76 versus 0.59; p = 0.0097). At the cut-off point with the maximal positive predictive value 2% of the patients scored positive, at the cut-off point with the maximal negative predictive value pulmonary embolism could be excluded in 16% of the patients. Conclusions: We derived a simple decision rule containing 5 easily interpretable variables for the patient population specified. The optimal use of the rule appears to be in the exclusion of pulmonary embolism. Prospective validation of this rule is indicated to confirm its clinical utility.

The Evolutionary Dynamics of Decision Rule Selection

2017 ◽  
Author(s):  
Michael Laver ◽  
Ernest Sergenti
Keyword(s):  
Decision Rule ◽  
Positive Feedback ◽  
Party System ◽  
Evolutionary Dynamics ◽  
Decision Rules ◽  
Past Performance ◽  
Party Leaders ◽  
Track Record ◽  
Long Run ◽  
Survival Of The Fittest

This chapter extends the survival-of-the-fittest evolutionary environment to consider the possibility that new political parties, when they first come into existence, do not pick decision rules at random but instead choose rules that have a track record of past success. This is done by adding replicator-mutator dynamics to the model, according to which the probability that each rule is selected by a new party is an evolving but noisy function of that rule's past performance. Estimating characteristic outputs when this type of positive feedback enters the dynamic model creates new methodological challenges. The simulation results show that it is very rare for one decision rule to drive out all others over the long run. While the diversity of decision rules used by party leaders is drastically reduced with such positive feedback in the party system, and while some particular decision rule is typically prominent over a certain period of time, party systems in which party leaders use different decision rules are sustained over substantial periods.

Endogenous Parties, Interaction of Different Decision Rules

2017 ◽  
Author(s):  
Michael Laver ◽  
Ernest Sergenti
Keyword(s):  
Decision Rule ◽  
Decision Rules ◽  
Party Competition ◽  
Competitive Environment ◽  
Party Leaders ◽  
Robert Axelrod

This chapter attempts to develop more realistic and interesting models in which the set of competing parties is a completely endogenous output of the process of party competition. It also seeks to model party competition when different party leaders use different decision rules in the same setting by building on an approach pioneered in a different context by Robert Axelrod. This involves long-running computer “tournaments” that allow investigation of the performance and “robustness” of decision rules in an environment where any politician using any rule may encounter an opponent using either the same decision rule or some quite different rule. The chapter is most interested in how a decision rule performs against anything the competitive environment might throw against it, including agents using decision rules that are difficult to anticipate and/or comprehend.

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