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Comparing Stochastic Design Decision Belief Models: Pointwise versus Interval Probabilities

Matthews, P.C.



J.S. Gero


Decision support systems can either directly support a product designer or support an agent operating within a multi-agent system (MAS). Stochastic based decision support systems require an underlying belief model that encodes domain knowledge. The underlying supporting belief model has traditionally been a probability distribution function (PDF) which uses pointwise probabilities for all possible outcomes. This can present a challenge during the knowledge elicitation process. To overcome this, it is proposed to test the performance of a credal set belief model. Credal sets (sometimes also referred to as p-boxes) use interval probabilities rather than pointwise probabilities and therefore are more easier to elicit from domain experts. The PDF and credal set belief models are compared using a design domain MAS which is able to learn, and thereby refine, the belief model based on its experience. The outcome of the experiment illustrates that there is no significant difference between the PDF based and credal set based belief models in the performance of the MAS.


Matthews, P. (2010). Comparing Stochastic Design Decision Belief Models: Pointwise versus Interval Probabilities. In J. Gero (Ed.),

Conference Name 4th International Conference on Design Computing and Cognition DCC'10
Conference Location Stuttgart, Germany
Start Date Jul 12, 2010
End Date Jul 14, 2010
Publication Date Jul 1, 2010
Deposit Date Jul 20, 2010
Publicly Available Date Jul 23, 2010
Publisher Springer Verlag
Pages 327-345
Series Title Design Computing and Cognition
Public URL
Publisher URL
Additional Information Conference date: 12–14 July 2010


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