Title :
Objective evaluation of subjective decisions
Author :
Siegel, Mel ; Wu, Huadong
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
fDate :
5/17/2003 12:00:00 AM
Abstract :
The Dempster-Shafer "theory of evidence" encompasses and extends the Bayes theorem-based decision making machinery. Dempster-Shafer\´s innovation is the introduction of lower and upper bounds, designated "belief" and "plausibility", that are attached to probability estimates. The Dempster-Shafer algebra provides for propagation and reasoning about these quantities according to an algebra whose outcome phenomenologically mimics human decision making in many contexts that are laden with quantitative uncertainty. The approach\´s decision seem to be subjective, i.e., the product of a sentient mind, vs. objective, i.e., the mechanical outcome of an immutable algorithm. In this paper, we address the "objective evaluation of subjective decisions" in particular with the Dempster-Shafer sort of "subjective" decision making algorithm in mind. As an initial baseline approach, we examine the "receiver operating characteristic" (ROC) graph. We regard this as a first step towards identifying in advance circumstances under which Dempster-Shafer-like approaches should and should not be expected to deliver results that pass the human "sanity test".
Keywords :
belief maintenance; decision making; decision theory; inference mechanisms; learning (artificial intelligence); sensitivity analysis; uncertainty handling; Bayes Theorem; Dempster-Shafer algebra; Dempster-Shafer theory; belief; decision making machinery; human decision making; immutable algorithm; objective decision; objective evaluation; plausibility; probability estimate; propagation; quantitative uncertainty; reasoning; receiver operating characteristic graph; sanity test; sentient mind; subjective decision; theory of evidence; Algebra; Context awareness; Decision making; Humans; Machinery; Medical diagnosis; Robots; Sensor fusion; Sensor systems; Working environment noise;
Conference_Titel :
Soft Computing Techniques in Instrumentation, Measurement and Related Applications, 2003. SCIMA 2003. IEEE International Workshop on
Print_ISBN :
0-7803-7711-7
DOI :
10.1109/SCIMA.2003.1215924