經濟學系講座: A Complexity Hierarchy for Stochastic Choice
講者: 楊爾雅教授, 助理教授, 商學院, 中山大學
日期：11/09/2024(三)
時間：14:00 – 15:15
地點: E21B-G002
語言: 英語
內容: We develop a hierarchy of families of stochastic choice rules in terms of increasing complexity based on the concepts of a conditional probability space (R’enyi, 1955) and a dimensionally-ordered system of measures (R’enyi, 1956). The levels of our hierarchy are: single-valued or point conditional probability spaces (PCPS’s); conditional probability spaces; probabilistic mixtures of PCPS’s; mutually absolutely continuous mixtures of PCPS’s; absolutely continuous mixtures of PCPS’s; and signed probability mixtures of PCPS’s. We show at a general measure-theoretic level that the first five levels are strictly nested. In the finite case, the sixth level nests all the other levels (the general case here appears to be open). Our hierarchy organizes various well-known axioms for stochastic choice and identifies some new relationships among them. It also offers a precise definition of contextuality in stochastic choice and, from this, a new classification of some leading behavioral effects in choice.
