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Unexpectedness is a central concept in Simplicity Theory, a theory of cognition relating various inferential processes to the computation of Kolmogorov complexities, rather than probabilities. Its predictive power has been confirmed by…

Artificial Intelligence · Computer Science 2023-11-16 Giovanni Sileno , Jean-Louis Dessalles

Pothos & Busemeyer's (P&B's) query about whether quantum probability can provide a foundation for the cognitive modeling embodies so many underlying implications that the subject is far from exhausted. In this brief commentary, however, I…

Neurons and Cognition · Quantitative Biology 2016-09-05 Alexandre de Castro

The established language for statistical testing --- significance levels, power, and p-values --- is overly complicated and deceptively conclusive. Even teachers of statistics and scientists who use statistics misinterpret the results of…

Statistics Theory · Mathematics 2019-10-23 Glenn Shafer

A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction, disjunction, inverse, and conditional fallacies, as well as unpacking effects and partitioning effects. Quantum…

General Physics · Physics 2009-09-16 Jerome R. Busemeyer , Riccardo Franco , Emmanuel M. Pothos

A general notion of algebraic conditional plausibility measures is defined. Probability measures, ranking functions, possibility measures, and (under the appropriate definitions) sets of probability measures can all be viewed as defining…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern

This paper provides an analysis of different formal representations of beliefs in epistemic game theory. The aim is to attempt a synthesis of different structures of beliefs in the presence of indeterminate probabilities. Special attention…

Computer Science and Game Theory · Computer Science 2013-09-09 Yang Liu

This chapter presents probability logic as a rationality framework for human reasoning under uncertainty. Selected formal-normative aspects of probability logic are discussed in the light of experimental evidence. Specifically, probability…

Artificial Intelligence · Computer Science 2019-10-16 Niki Pfeifer

Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision…

Computer Science and Game Theory · Computer Science 2023-06-22 Philippe Mongin

In statistical practice, whether a Bayesian or frequentist approach is used in inference depends not only on the availability of prior information but also on the attitude taken toward partial prior information, with frequentists tending to…

Statistics Theory · Mathematics 2012-05-02 David R. Bickel

After making some general remarks, I consider two examples that illustrate the use of Bayesian Probability Theory. The first is a simple one, the physicist's favorite "toy," that provides a forum for a discussion of the key conceptual issue…

High Energy Physics - Phenomenology · Physics 2007-05-23 Harrison B. Prosper

In this work we first illustrate the subjective theory of de Finetti. We recall the notion of coherence for both the betting scheme and the penalty criterion, by considering the unconditional and conditional cases. We show the equivalence…

Probability · Mathematics 2023-01-24 Angelo Gilio , Giuseppe Sanfilippo

When humans infer underlying probabilities from stochastic observations, they exhibit biases and variability that cannot be explained on the basis of sound, Bayesian manipulations of probability. This is especially salient when beliefs are…

Neurons and Cognition · Quantitative Biology 2021-07-08 Arthur Prat-Carrabin , Florent Meyniel , Misha Tsodyks , Rava Azeredo da Silveira

We consider a conception of reality that is the following: An object is 'real' if we know that if we would try to test whether this object is present, this test would give us the answer 'yes' with certainty. If we consider a conception of…

Quantum Physics · Physics 2017-08-23 Diederik Aerts

How can probabilities make sense in a deterministic many-worlds theory? We address two facets of this problem: why should rational agents assign subjective probabilities to branching events, and why should branching events happen with…

Quantum Physics · Physics 2019-03-26 Mateus Araújo

This contribution derives from a rather extensive study on the foundations of probability. We start by discussing critically the two main models of the random event in Probability Theroy and cast light over a number of incongruities. We…

Probability · Mathematics 2007-05-23 Paolo Rocchi , Leonida Gianfagna

In the absence of empirical confirmation, scientists may judge a theory's chances of being viable based on a wide range of arguments. The paper argues that such arguments can differ substantially with regard to their structural similarly to…

History and Philosophy of Physics · Physics 2017-02-07 Richard Dawid

The role of probability appears unchallenged as the key measure of uncertainty, used among other things for practical induction in the empirical sciences. Yet, Popper was emphatic in his rejection of inductive probability and of the logical…

Other Statistics · Statistics 2021-08-04 Youngjo Lee , Yudi Pawitan

In the Quantum-Bayesian interpretation of quantum theory (or QBism), the Born Rule cannot be interpreted as a rule for setting measurement-outcome probabilities from an objective quantum state. But if not, what is the role of the rule? In…

Quantum Physics · Physics 2015-06-12 Christopher A. Fuchs , Ruediger Schack

The subjective and the objective aspects of probabilities are incorporated in a simple duality axiom inspired by observer participation in quantum theory. Transcending the classical notion of probabilities, it is proposed and demonstrated…

Quantum Physics · Physics 2013-03-20 Rajat Kumar Pradhan

Reasoning about degrees of belief in uncertain dynamic worlds is fundamental to many applications, such as robotics and planning, where actions modify state properties and sensors provide measurements, both of which are prone to noise. With…

Artificial Intelligence · Computer Science 2013-09-27 Vaishak Belle , Hector Levesque