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主讲人简介

Fabio Maccheroni，1999年获得应用数学博士学位，现任博科尼大学（Università Bocconi）决策科学系（Department of Decision Sciences）教授，IGIER研究中心会员，主要研究领域包括经济理论、决策分析、概率论等，曾在American Economic Review，Econometrica，The Review of Economic Studies，Theory and Decision，Management Science等国际顶级学术期刊发表学术论文数十篇，先后受邀在剑桥大学、加州理工大学、普林斯顿高等研究院、帝国理工学院等多所世界著名高校举办讲座和研讨会。2010年Fabio Maccheroni教授荣获卡洛·阿尔贝托奖，该奖项旨在授予在经济学领域做出杰出研究贡献的40岁以下意大利经济学家。

专题课程概要

Many crucial choices we make (both in our professional life and in our personal development) involve uncertainty. This tutorial introduces a language for describing uncertain choice situations, describes some classical decision criteria, and explains how they can be made "robust to uncertainty". These criteria and their features are then illustrated with cases from Economics, Engineering, and Medicine.

学术沙龙概要

The softmax model (also known as Multinomial Logit Model or Power Luce Model) is the most widely used model of preference discovery in all fields of decision making, from Quantal Response Equilibria to Discrete Choice Analysis, from Psychophysics and Neuroscience to Combinatorial Optimization. Our axiomatic characterization of softmax permits to empirically test its descriptive validity and to better understand its conceptual underpinnings as a theory of agents rationality. Our neuropsychological foundation provides a computational model that may explain softmax emergence in human multialternative choice behavior and that naturally extends the dominant Diffusion Model paradigm of binary choice.

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