Title
How far to commit to open-loop action: a probabilistic decision approach with analogies to signal-detection theory
Abstract
A theory for optimizing the extent of a continuous action variable in a situation where either or both a discrete reward and discrete cost occur as probabilistic functions of the extent of the action selected is presented. It is shown how in many respects the approach is similar to signal detection theory, and also that there are the essential differences, especially since the decision is continuous rather than binary. Examples for application are suggested
Year
DOI
Venue
1993
10.1109/21.256560
Systems, Man and Cybernetics, IEEE Transactions  
Keywords
Field
DocType
decision theory,probability,signal detection,discrete cost,discrete reward,open-loop action,probabilistic decision,probabilistic functions,signal detection theory
Mathematical optimization,Human operator,Detection theory,Commit,Computer science,Decision theory,Decision model,Probabilistic logic,Open-loop controller,Binary number
Journal
Volume
Issue
ISSN
23
3
0018-9472
Citations 
PageRank 
References 
1
0.35
0
Authors
1
Name
Order
Citations
PageRank
Thomas B. Sheridan1706254.65