Preference Function Modelling: The Mathematical Foundations of Decision Theory

2010 ◽  
pp. 57-86 ◽  
Author(s):  
Jonathan Barzilai
Keyword(s):  
Decision Theory ◽  
Preference Function ◽  
Function Modelling ◽  
Mathematical Foundations

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

Giving advice: Decision theory perspectives on sexual assault.

1992 ◽  
Vol 47 (4) ◽  
pp. 577-588 ◽  
Author(s):  
Baruch Fischhoff
Keyword(s):  
Sexual Assault ◽  
Decision Theory

Rational Uses of Decision Theory

PsycCRITIQUES ◽  
2009 ◽  
Vol 54 (42) ◽  
Author(s):  
Gordon Pitz
Keyword(s):  
Decision Theory

The Measurement of Performance in Probabilistic Diagnosis IV. Utility Considerations in Therapeutics and Prognostics

1981 ◽  
Vol 20 (02) ◽  
pp. 80-96 ◽  
Author(s):  
J. D. F. Habbema ◽  
J. Hilden
Keyword(s):  
Decision Theory ◽  
Figure Of Merit ◽  
Acute Abdominal Pain ◽  
Theory Approach ◽  
Expected Loss ◽  
Patient Benefit ◽  
Evaluation Approach ◽  
Average Loss ◽  
Actual Decision ◽  
Probabilistic Diagnosis

It is argued that it is preferable to evaluate probabilistic diagnosis systems in terms of utility (patient benefit) or loss (negative benefit). We have adopted the provisional strategy of scoring performance as if the system were the actual decision-maker (not just an aid to him) and argue that a rational figure of merit is given by the average loss which patients would incur by having the system decide on treatment, the treatment being selected according to the minimum expected loss principle of decision theory.A similar approach is taken to the problem of evaluating probabilistic prognoses, but the fundamental differences between treatment selection skill and prognostic skill and their implications for the assessment of such skills are stressed. The necessary elements of decision theory are explained by means of simple examples mainly taken from the acute abdomen, and the proposed evaluation tools are applied to Acute Abdominal Pain data analysed in our previous papers by other (not decision-theoretic) means. The main difficulty of the decision theory approach, viz. that of obtaining good medical utility values upon which the analysis can be based, receives due attention, and the evaluation approach is extended to cover more realistic situations in which utility or loss values vary from patient to patient.

The Process of Medical Diagnosis: Routes of Mathematical Investigations

1978 ◽  
Vol 17 (01) ◽  
pp. 1-10 ◽  
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Decision Theory ◽  
Medical Diagnosis ◽  
Pattern Analysis ◽  
Logical Probability ◽  
Inquiry Process ◽  
Fuzzy Subsets

This paper is an analysis of the most important mathematical aspects of medical diagnosis: logical probability, rationality and decision theory, gambling models, pattern analysis, hazy and fuzzy subsets theory and, finally, the stochastic inquiry process.

Sign in / Sign up

Export Citation Format

Share Document