Multiple Criteria Decision Analysis and Multiple Criteria Decision Theory

Fabio Maccheroni

Fabio Maccheroni
Principal Investigator

Team Members: Emanuele Borgonovo, Simone Cerreia-Vioglio, Paolo Leonetti, Massimo Marinacci

MIUR PRIN 2017
April 2020 - April 2024

Abstract

The pervasiveness of the problem of decision making at all levels of human activity stimulated the research of the best economists, mathematicians and statisticians of the last century: John von Neumann, Oscar Morgenstern, Abraham Wald, Leonard Savage, Duncan Luce, Howard Raiffa and Daniel McFadden, just to cite some of them. Their efforts produced the formal structures which are at the foundations of both Decision Theory (DT) and Decision Analysis (DA), fields that initially shared the same framework, principles and methods. Yet, subsequently, DT and DA developed in different directions:

  • the former followed a more theoretical approach with a focus on decisions under uncertainty and the different descriptions and features of uncertainty itself, 
  • the latter tackled the operational side of decision problems with the aim of providing support to individuals and policy makers, giving special attention to the multiplicity of criteria typical of real life choice situations. 

The augmented complexity of decision challenges (ranging from catastrophic risks to artificial intelligence) and their management call for a reunification of DT and DA with the objective of mutual renewal and enhancement, permitting to take effectively into account multifaceted uncertainties and their multidimensional consequences. This would stimulate the adherence to reality of DT models, on one hand, and the empowerment of DA with new and robust tools on the other. 

The reunification we aim at, although ambitious, is an attainable result. Even if the two fields proceeded in parallel, several similarities can be found in their recent developments. Among others, it is noticeable the common focus on the need of robustness, made necessary -- inter alia -- by the scarcity or unreliability of available information based on which decisions have to be taken and by the high stakes of decisions' consequences. An example of this common concern for robustness can be found in the closely related concepts of "Bewleyan and justifiable preferences" in Decision Theory under uncertainty and the concepts of "necessary and possible preferences" in multiple criteria decision analysis. 

With these premises, the objectives of this research are: 

  • To lay the foundation for a shared language and a common approach to Decision Theory and Decision Analysis, that incorporates the recent developments of both fields, with a special emphasis on the common normative aspects and the common need of robustness. 
  • To study decision frameworks that are able to take into account both several layers and types of uncertainty and a multiplicity of criteria at the same time.

Other Research Unit:

  • Università degli Studi di Catania - coordinator: Salvatore Greco
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This project has been funded by Ministero dell'Istruzione, dell'Università e della Ricerca under the framework PRIN 2017 - Progetti di ricerca di Rilevante Interesse Nazionale.