Reframing Decision Problems : A Graph-Grammar Approach
One fundamental requirement in the expected utility model is that the preferencesof rational persons should be independent of problem description. Yet an extensivebody of research in descriptive decision theory indicates precisely the opposite: whenthe same problem is cast in two different, but normatively equivalent, quot;frames,quot;people tend to change their preferences in a systematic and predictable way. In particular,alternative frames of the same decision tree are likely to invoke different setsof heuristics, biases, and risk-attitudes, in the user's mind. The paper presents a computationalmodel in which decision-trees are cast as attributed graphs, and reframingoperations on trees are implemented as graph-grammar productions. In addition tothe basic functions of creating and analyzing decision-trees, the model offers a naturalway to define a host of quot;debiasing mechanismsquot; using graphical programming techniques,Some of these mechanisms have appeared in the decision theory literature,whereas others were directly inspired by the novel use of graph grammars in modelingdecision problems