On the Qualitative Comparison of Decisions Having Positive and Negative Features
Making a decision is often a matter of listing and comparing positive and negative arguments. In such cases, the evaluation scale for decisions should be considered bipolar, that is, negative and positive values should be explicitly distinguished. That is what is done, for example, in Cumulative Prospect Theory. However, contraryto the latter framework that presupposes genuine numerical assessments, human agents often decide on the basis of an ordinal ranking of the pros and the cons, and by focusing on the most salient arguments. In other terms, the decision process is qualitative as well as bipolar. In this article, based on a bipolar extension of possibility theory, we define and axiomatically characterize several decision rules tailored for the joint handling of positive and negative arguments in an ordinal setting. The simplest rules can be viewed as extensions of the maximin and maximax criteria to the bipolar case, and consequently suffer from poor decisive power. More decisive rules that refine the former are also proposed. These refinements agree both with principles of efficiency and with the spirit of order-of-magnitude reasoning, that prevails in qualitative decision theory. The most refined decision rule uses leximin rankings of the pros and the cons, and the ideas of counting arguments of equal strength and cancelling pros by cons. It is shown to come down to a special case of Cumulative Prospect Theory, and to subsume the Take the Best heuristic studied by cognitive psychologists.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Identifying the Effect of Parenthood on Labor Force Participation: A Gender Comparison
Identifying the factors that influence labor force participation could elucidate how individuals arrive at their labor supply decisions, whose understanding is, in turn, of crucial importance in analyzing how the supply …
Syntactic Framing Fragility: An Audit of Robustness in LLM Ethical Decisions
Large language models exhibit systematic negation sensitivity, yet no operational framework exists to measure this vulnerability at deployment scale, especially in high-stakes decisions. We introduce Syntactic Framing Fr…
Modelling stock correlations with expected returns from investors
Stock correlations is crucial to asset pricing, investor decision-making, and financial risk regulations. However, microscopic explanation based on agent-based modeling is still lacking. We here propose a model derived f…
Decision MakingDemocratic Favor Channel
A large body of literature in economics and political science examines the impact of democracy and political freedoms on various outcomes using cross-country comparisons. This paper explores the possibility that any posi…
PhilosophyIlluminating Salient Contributions in Neuron Activation with Attribution Equilibrium
With the remarkable success of deep neural networks, there is a growing interest in research aimed at providing clear interpretations of their decision-making processes. In this paper, we introduce Attribution Equilibriu…
Decision Making