The study of prescriptive and descriptive models of decision making
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2012, Vol 1, Issue 1
Abstract
The field of decision making can be loosely divided into two parts: the study of prescriptive models and the study of descriptive models. Prescriptive decision scientists are concerned with prescribing methods for making optimal decisions. Descriptive decision researchers are concerned with the bounded way in which the decisions are actually made. The statistics courses treat risk from a prescriptive, by suggesting rational methods. This paper brings out the work done by many researchers by examining the psychological factors that explain how managers deviate from rationality in responding to uncertainty.
Authors and Affiliations
Prof. Ashok A. Divekar , Prof. Sunita Bangal , Prof. Sumangala D.
Keywords
Related Articles
- EP ID EP135100
- DOI -
- Views 112
- Downloads 0
Cogntive Consistency Analysis in Adaptive Bio-Metric Authentication System Design
Cognitive consistency analysis aims to continuously monitor one's perception equilibrium towards successful accomplishment of cognitive task. Opposite to cognitive flexibility analysis – cognitive consistency analy...
A Comparison between Regression, Artificial Neural Networks and Support Vector Machines for Predicting Stock Market Index
Obtaining accurate prediction of stock index sig-nificantly helps decision maker to take correct actions to develop a better economy. The inability to predict fluctuation of the stock market might cause serious pro...
WSDF: Weighting of Signed Distance Function for Camera Motion Estimation in RGB-D Data
With the recent advent of the cost-effective Kinect, which can capture real-time high-resolution RGB and visual depth information, has opened an opportunity to significantly increase the capabilities of many automa...
Algorithm for Design of Digital Notch Filter Using Simulation
A smooth waveform is generated of low frequency signal can be achieved through the Digital Notch Filter. Noise can be easily eliminated from a speech signal by using a Notch filter. In this paper the design of notch filt...
Density Based Support Vector Machines for Classification
Support Vector Machines (SVM) is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification) of training points. However, sometimes there...