Invited Talks and Contributions at ISIPTA '03

We are proud to announce the following three invited talks/contributions at ISIPTA '03. These are included in the (regular or student) registration fee. You are kindly invited to participate.

Prof. Fine's banquet talk

SPEAKER: Terrence L. Fine, Professor of Electrical & Computer Engineering and Statistical Science, School of Electrical and Computer Engineering and Center for Applied Mathematics, Cornell University, USA.
TITLE: Theories of Probability: Some Questions about Foundations.
SLIDES: Get a pdf file with talk slides.
ABSTRACT:
We consider some of the following questions and offer some thoughts but no answers.
How do we recognize probabilistic reasoning and its armature of probability theory?
How is the study of probabilistic reasoning distinguished from study of other forms of indeterminacy, imprecision, and vagueness?
Methodology or theory?
What counts as a theory of probability and what does not?
Is there a unified concept of probability?
Is probability fundamental or is it merely a convenient placeholder for a more detailed account?
Can we judge ``adequacy'' (satisfaction, success) outside of the very methodology/theory of probability we are using?
Is a pragmatic stance sufficient or merely defeatist?
Is self-consistency sufficient or at most necessary?
What are examples of domains, however small, and probability theories for them that are unproblematic?
What are examples of conceptual frameworks or spaces within which to have this discussion?

Prof. Good's contribution

SPEAKER: Irving J. Good, University Distinguished Professor Emeritus, Virginia Tech., USA.
(Unfortunately, Prof. Good will be unable to come to Lugano for ISIPTA '03, but he should be available to reply to questions the attendees will raise on his contribution.)
TITLE: The Accumulation of Imprecise Weights of Evidence.
PAPER: Get a pdf file with the contribution.
ABSTRACT:
A familiar method for modeling imprecise or partially ordered probabilities is to regard them as interval valued. It is proposed here that it is better to assume a Gaussian form for the logarithm of the probabilities. To fix the hyperparameters of the Gaussian curve one could make judgements for the quartiles for example. The same comment applies for weights of evidence. The reason for this proposal is that when the pieces of evidence are statistically independent one has additivity and the addition of Gaussian curves is easy to perform. When the pieces of evidence are dependent, there is a more general additivity, or one might be able to allow for interactions of various orders. Possible applications would be to legal trials and to differential diagnosis in medicine, or even for distinguishing between two hypotheses in general.

Prof. Suppes' talk

SPEAKER: Patrick Suppes, Lucie Stern Professor of Philosophy, Emeritus, Stanford University, USA.
TITLE: Application of Nonmonotonic Upper Probabilities to Quantum Entanglement.
SLIDES: Get a pdf file with talk slides.
ABSTRACT:
A well-known property of quantum entanglement phenomena is that random variables representing the observables in a given experiment do not have a joint probability distribution. The main point of this lecture is to show how a generalized distribution, which is a nonmonotonic upper probability distribution, can be used for all the observables in two important entanglement cases: the four random variables or observables used in Bell-type experiments and the six correlated spin observables in three-particle GHZ-type experiments. Whether or not such upper probabilities can play a significant role in the conceptual foundations of quantum entanglement will be discussed.