Skip navigation
Please use this identifier to cite or link to this item:
Title: Randomness in Limited Information Based Decisionmaking
Authors: Dasarathy, Anirudh
Advisors: Pesendorfer, Wolfgang
Department: Operations Research and Financial Engineering
Class Year: 2016
Abstract: Standard decision-making theory assumes that an agent considers all possible alternatives when determining their final choice. However, in reality, agents do not truly consider all options but rather a select subset. Previous literature lays a framework for decision making theory based on such an assumption. This paper explores and develops two extensions. First, this paper recognizes that the order in which a user is presented with choices can affect their choice due to the dependency of the elements that are considered upon the ordering of elements. Second, this paper recognizes that the ordering that a user faces is random and subject to some probability distribution. Using these two assumptions, this paper develops a number of results that provide conditions under which an analyst may view the final choice of a user for any given permutation of elements from which the underlying preferences can be deduced. This paper then develops a plausible model for the manner in which humans pay attention to elements and demonstrates how the earlier results in the manuscript can be used to deduce underlying preferences based on observational data.
Extent: 43 pages
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2016

Files in This Item:
File SizeFormat 
DasarathyAnirudh_final_thesis.pdf329.28 kBAdobe PDF    Request a copy

Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.