Deep Models of Decision
Federico Tiblias
Deep Models of Decision.
Rel. Bartolomeo Montrucchio. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2023
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Abstract
Decision Theory is a branch of mathematics and economics that studies the process of decision-making under uncertainty. It provides a framework for analyzing the choices made by individuals or organizations and gives guidance on how to make the best decisions possible given the limited information and resources available. Choice Modeling is a subfield of Decision Theory that aims to explain and measure how people or groups make decisions when presented with various options. It achieves this by modeling the link between the characteristics of those options and the likelihood that a person will select one over another. Some of its applications include analyzing consumer behavior in marketing research, predicting voter preferences in political campaigns, optimizing public policy decisions, and designing recommendation systems for online platforms.
The main goal of this thesis is to propose and assess novel approaches to Choice Modeling that leverage the expressivity of deep machine learning models
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