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We revisit the role of instrumental value as a driver of adaptive behavior. In active inference, instrumental or extrinsic value is quantified by the information-theoretic surprisal of a set of observations measuring the extent to which…

Neurons and Cognition · Quantitative Biology 2020-10-14 Alvaro Ovalle , Simon M. Lucas

State-of-the-art multi-objective optimization often assumes a known utility function, learns it interactively, or computes the full Pareto front-each requiring costly expert input.~Real-world problems, however, involve implicit preferences…

Machine Learning · Computer Science 2025-10-01 Farha A. Khan , Tanmay Chakraborty , Jörg P. Dietrich , Christian Wirth

Shafer's theory of belief and the Bayesian theory of probability are two alternative and mutually inconsistent approaches toward modelling uncertainty in artificial intelligence. To help reduce the conflict between these two approaches,…

Artificial Intelligence · Computer Science 2013-03-08 Robert F. Bordley

We study a \emph{financial} version of the classic online problem of scheduling weighted packets with deadlines. The main novelty is that, while previous works assume packets have \emph{fixed} weights throughout their lifetime, this work…

Computer Science and Game Theory · Computer Science 2025-02-21 Yotam Gafni , Aviv Yaish

The concept of time mostly plays a subordinate role in finance and economics. The assumption is that time flows continuously and that time series data should be analyzed at regular, equidistant intervals. Nonetheless, already nearly 60…

Statistical Finance · Quantitative Finance 2024-06-12 James B. Glattfelder , Richard B. Olsen

Although many investigators affirm a desire to build reasoning systems that behave consistently with the axiomatic basis defined by probability theory and utility theory, limited resources for engineering and computation can make a complete…

Artificial Intelligence · Computer Science 2013-04-11 Eric J. Horvitz

In this paper an approach to automated deduction under uncertainty,based on possibilistic logic, is proposed ; for that purpose we deal with clauses weighted by a degree which is a lower bound of a necessity or a possibility measure,…

Artificial Intelligence · Computer Science 2013-04-08 Didier Dubois , Jerome Lang , Henri Prade

In this paper we consider the statistical inference of the unknown parameter of an exponential distribution based on the time truncated data. The time truncated data occurs quite often in the reliability analysis for type-I or hybrid…

Applications · Statistics 2017-03-06 Arnab Koley , Debasis Kundu

This paper relates both to the metaphysics of probability and to the physics of time asymmetry. Using the formalism of decoherent histories, it investigates whether intuitions about intrinsic time directedness that are often associated with…

Quantum Physics · Physics 2007-05-23 Guido Bacciagaluppi

In this work we present an epistemic analysis of time phenomenon using the mathematical machinery of information theory and modular theory. By adopting limited commitment to the ontology of time evolution, and instead by mainly relying on…

History and Philosophy of Physics · Physics 2022-06-09 Farhang Hadad Farshi , Silvia DeBianchi

We demonstrate that temporal observables, which are sensitive to a system's history (as opposed to its state), implicate entangled histories. We exemplify protocols for measuring such observables, and algorithms for predicting the…

Quantum Physics · Physics 2017-02-21 Jordan Cotler , Frank Wilczek

Representing token embeddings as probability distributions over learned manifolds allows for more flexible contextual inference, reducing representational rigidity while enhancing semantic granularity. Comparative evaluations demonstrate…

Computation and Language · Computer Science 2025-04-25 Christopher Nightingale , Dominic Lavington , Jonathan Thistlethwaite , Sebastian Penhaligon , Thomas Belinski , David Boldo

Suspense is a crucial ingredient of narrative fiction, engaging readers and making stories compelling. While there is a vast theoretical literature on suspense, it is computationally not well understood. We compare two ways for modelling…

Computation and Language · Computer Science 2020-05-01 David Wilmot , Frank Keller

In simple -- but selected -- quantum systems, the probability distribution determined by the ground state wave function is infinitely divisible. Like all simple quantum systems, the Euclidean temporal extension leads to a system that…

Quantum Physics · Physics 2007-05-23 John R. Klauder

In stochastic decision problems, one often wants to estimate the underlying probability measure statistically, and then to use this estimate as a basis for decisions. We shall consider how the uncertainty in this estimation can be…

Statistics Theory · Mathematics 2017-05-24 Samuel N. Cohen

The focus of the current work concerned the psychological processes that underlie prediction of an events duration. The objective was to push forward existing psychological theory on event duration prediction, something made possible by the…

Human-Computer Interaction · Computer Science 2025-09-19 Mark G Orr

Since Leonard Savage's epoch-making "Foundations of Statistics", Subjective Expected Utility Theory has been the presumptive model for decision-making. Savage provided an act-based axiomatization of standard expected utility theory. In this…

Artificial Intelligence · Computer Science 2018-02-12 Grant Molnar

It is a commonplace perception that speed of time subjectively experienced by humans significantly differs from chronological (objective) time and shows a great deal of variability. An often cited example is the phenomenon of the time…

Physics and Society · Physics 2023-10-11 Vladimir Shiltsev

We exploit qualitative probabilistic relationships among variables for computing bounds of conditional probability distributions of interest in Bayesian networks. Using the signs of qualitative relationships, we can implement abstraction…

Artificial Intelligence · Computer Science 2013-02-01 Chao-Lin Liu , Michael P. Wellman

We give a probabilistic analysis of inductive knowledge and belief and explore its predictions concerning knowledge about the future, about laws of nature, and about the values of inexactly measured quantities. The analysis combines a…

Logic in Computer Science · Computer Science 2021-06-23 Jeremy Goodman , Bernhard Salow