The Mathematics of Subjective Probability
MSP 2018 - Milan, 03/09 to 05/09 2018
Building 4, Room 08, piazza della Scienza 1
The subjective approach to probability has historically had great importance in the comprehension of uncertainty phenomena, as witnessed by the works of de Finetti, Dubins, Savage and of too many other scholars to mention explicitly.
Although mostly superseded by the axiomatic setting inaugurated by Kolmogoroff, the subjective approach is common to all those studies in which probability is not taken as an assumption but rather as part of the solution to specific mathematical problems in statistics, decision theory, gambling, game theory, economics.
In organizing this meeting we aim at putting together researchers who, each in his own field, share such fundamental view and at bringing to the general attention the work done so far and the great future potential.
The Mathematics of Subjective Probability' workshop -- hopefully only a first event of a future series -- welcomes all mathematicians who are interested in the topic.
MSP invites submissions of papers dealing with a variety of topics which include (but are not limited to):
- Bayesian statistics;
- Decision models under risk and uncertainty;
- Equivalent martingale measures;
- Finitely additive probabilities;
- Game Theory;
- Limit theorems;
- Mass transportation;
- Merging of opinions;
- Multiple priors;
- Partial knowledge.
Organizing Committee: Gianluca Cassese (Università Bicocca, Milano), Pietro Rigo (Università di Pavia), Barbara Vantaggi (Università "La Sapienza", Roma).
Scientific Committee: Patrizia Berti, Gianluca Cassese, Itzhak Gilboa, Giovanna Iannantuoni, Antonio Lijoi, Pietro Rigo, Fabio Spizzichino, Barbara Vantaggi.
Proceedings: The Springer journal Decisions in Economics and Finance plans to devote a special issue for the workshop.
Università Bicocca - Dipartimento di Economia (DEMS)
Università di Pavia - Dipartimento di Matematica "F. Casorati"
Università "L. Bocconi" - Dipartimento di Scienza delle Decisioni
We acknowledge financial support from PRIN 2015SNS29B_002: "Modern Bayesian nonparametric methods".