International audienceCase-Based Decision Theory (CBDT) postulates that decision making under uncertainty is based on analogies to past cases. In its original version, it suggests that each of the available acts is ranked according to its own performance in similar decision problems encountered in the past. The purpose of this paper is to extend CBDT to deal with cases in which the evaluation of an act may also depend on past performance of different, but similar acts. To this end we provide a behavioral axiomatic definition of the similarity function over problem-act pairs (and not over problem pairs alone, as in the original model). We propose a model in which preferences are context-dependent. For each conceivable history of outcomes (to...
We introduce a computer program which calculates an agent’s optimal behavior according to Case-based...
International audienceThis paper is an attempt at providing a fuzzy set-based approach to case-based...
Choice option similarity is a key contextual variable in multiattribute choice. Based on theories of...
International audienceCase-Based Decision Theory (CBDT) postulates that decision making under uncert...
International audienceThis paper provides two axiomatic derivations of a case-baseddecision rule. Ea...
International audienceThis paper suggests that decision-making under uncertainty is, at least partly...
International audienceCase-Based Decision Theory (CBDT) is a theory of decision making under uncerta...
Case-based decision theory (Gilboa and Schmeidler, 1995) predicts that given a new problem, a decisi...
Case-based decision theory (CBDT) provided a new way of revealing preferences, with decisions under ...
In most theories of choice under uncertainty, decision-makers are assumed to evaluate acts in terms ...
Gilboa and Schmeidler provide a new paradigm for modeling decision making under uncertainty. Case-ba...
We consider a decision-situation in which the available information is given by a data-set. The deci...
The semantics of similarity measures is studied and reduced to the evidence theory of Dempster and S...
The book presents an axiomatic approach to the problems of prediction, classification, and statistic...
We present a formal model of decision-making under uncertainty, a variant of Case-Based Decision The...
We introduce a computer program which calculates an agent’s optimal behavior according to Case-based...
International audienceThis paper is an attempt at providing a fuzzy set-based approach to case-based...
Choice option similarity is a key contextual variable in multiattribute choice. Based on theories of...
International audienceCase-Based Decision Theory (CBDT) postulates that decision making under uncert...
International audienceThis paper provides two axiomatic derivations of a case-baseddecision rule. Ea...
International audienceThis paper suggests that decision-making under uncertainty is, at least partly...
International audienceCase-Based Decision Theory (CBDT) is a theory of decision making under uncerta...
Case-based decision theory (Gilboa and Schmeidler, 1995) predicts that given a new problem, a decisi...
Case-based decision theory (CBDT) provided a new way of revealing preferences, with decisions under ...
In most theories of choice under uncertainty, decision-makers are assumed to evaluate acts in terms ...
Gilboa and Schmeidler provide a new paradigm for modeling decision making under uncertainty. Case-ba...
We consider a decision-situation in which the available information is given by a data-set. The deci...
The semantics of similarity measures is studied and reduced to the evidence theory of Dempster and S...
The book presents an axiomatic approach to the problems of prediction, classification, and statistic...
We present a formal model of decision-making under uncertainty, a variant of Case-Based Decision The...
We introduce a computer program which calculates an agent’s optimal behavior according to Case-based...
International audienceThis paper is an attempt at providing a fuzzy set-based approach to case-based...
Choice option similarity is a key contextual variable in multiattribute choice. Based on theories of...