报告题目 | Temporal oscillations in preference strength provide evidence for a quantum-Markov open system model of preference evolution | ||
报告人（单位） | Prof. Jerome R. Busemeyer 美国科学与艺术学院院士（Indiana University） | ||
点评人（单位） | 刘新旺教授（东南大学） | 点评人（单位） | 高星副教授（东南大学） |
时间地点 | Time: Oct 20, 2021 07:00 PM Beijing time (07:00 AM Eastern Time) Join Zoom Meeting（点击连接后需下载zoom客户端） https://cmu.zoom.us/j/96214778771?pwd=ZjVhSi9zMTE3SzRINmJURE1KdWhqQT09 Meeting ID: 962 1477 8771 Passcode: 700428 | ||
报告内容摘要 | |||
Abstract: abstract: We examined how preferences evolve across time in two new experiments, one using choices between restaurants and a second using choices between gambles. In both we observed that mean preference strength systematically oscillated over time and found that eliciting a choice early in time strongly affected the pattern of preference oscillation later in time. Preferences following choices oscillated between being stronger than those without prior choice and being weaker than those without choice. Markov processes, such as random walk models, have been successfully used by cognitive and neural scientists to model human choice behavior and decision time for over 50 years. Recently, quantum walk models have been introduced as an alternative way to model the dynamics of human choice and confidence across time. Our new findings point to the need for both types of processes, and what are called “open system” models provide a way to incorporate them both into a single process. The open system model incorporates two sources of uncertainty: epistemic uncertainty about what preference state a decision maker has at a particular point in time; and ontic uncertainty about what decision or judgment will be observed when a person has some preference state. Representing these two sources of uncertainty allows the model to account for the oscillations in preference as well as the effect of choice on preference formation. keywords: decision making, evidence accumulation, preference evolution, sequential sampling, Markov dynamics, quantum dynamics | |||
报告人简介 | |||
BiographyJerome R. Busemeyer received the B.A. degree from the University of Cincinnati, Cincinnati, OH, USA, and the M.A. and Ph.D. degrees in psychology from the University of South Carolina, Columbia, SC, USA.,He is currently Provost Professor with the Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA. He has, for a long time, been one of the world’s leading researchers in decision making. His influential decision field theory is a dynamic and stochastic model of decision making designed to describe the variability of human preferences and how these preferences evolve across time. During the past five years, he has pioneered a brand new theoretical approach based on quantum probability theory for understanding the failures of humans to make decisions on the basis of rational principles. His quantum-cognition approach involves systematic application of this alternative system of probability to explaining human decision making in the social and behavioral sciences. His applications and tests of his quantum-cognition theory have appeared in diverse settings, including effects of categorization on decision making, the nature of probability judgments, similarity judgments, and measurement order effects. The new ideas have been hugely influential, sparking international conferences, special issues of journals, and major books. | |||
