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We consider the problem of performing Bayesian inference in probabilistic models where observations are accompanied by uncertainty, referred to as "uncertain evidence." We explore how to interpret uncertain evidence, and by extension the…

Machine Learning · Statistics 2023-01-27 Andreas Munk , Alexander Mead , Frank Wood

An increasing number of scientific experiments support the view of perception as Bayesian inference, which is rooted in Helmholtz's view of perception as unconscious inference. Recent study of logic presents a view of logical reasoning as…

Artificial Intelligence · Computer Science 2026-02-24 Hiroyuki Kido

Underlying the theory of inferences, a primary task of logic is language analysis. Such a task can be understood as depending on a general theory of representation, taking as a starting point the idea that some entities (`` representations…

Logic in Computer Science · Computer Science 2023-07-21 Arnaud Plagnol

The dominant theories of rational choice assume logical omniscience. That is, they assume that when facing a decision problem, an agent can perform all relevant computations and determine the truth value of all relevant logical/mathematical…

Artificial Intelligence · Computer Science 2023-07-12 Caspar Oesterheld , Abram Demski , Vincent Conitzer

A central concept in active inference is that the internal states of a physical system parametrise probability measures over states of the external world. These can be seen as an agent's beliefs, expressed as a Bayesian prior or posterior.…

Artificial Intelligence · Computer Science 2021-12-28 Nathaniel Virgo , Martin Biehl , Simon McGregor

Given a set of conflicting arguments, there can exist multiple plausible opinions about which arguments should be accepted, rejected, or deemed undecided. We study the problem of how multiple such judgments can be aggregated. We define the…

Artificial Intelligence · Computer Science 2017-06-20 Edmond Awad , Richard Booth , Fernando Tohme , Iyad Rahwan

We present a logical framework that enables us to define a formal theory of computational trust in which this notion is analysed in terms of epistemic attitudes towards the possible objects of trust and in relation to existing evidence in…

Logic in Computer Science · Computer Science 2025-06-19 Francesco A. Genco

The Bayesian persuasion model studies communication between an informed sender and a receiver with a payoff-relevant action, emphasizing the ability of a sender to extract maximal surplus from his informational advantage. In this paper we…

Computer Science and Game Theory · Computer Science 2020-06-04 Ronen Gradwohl , Niklas Hahn , Martin Hoefer , Rann Smorodinsky

The question of whether AI systems have morally relevant interests -- the 'model welfare' question -- depends in part on how we evaluate AI testimony about inner states. This paper develops what I call the inconsistency critique:…

Computers and Society · Computer Science 2026-01-15 Gerol Petruzella

Motivated by the forensic problem of determining the strength of evidence of a continuously distributed measurement of evidence, in the situation of composite hypotheses of the prosecutor and the defence concerning a parameter of a…

Applications · Statistics 2018-02-02 Bert van Es

The problem of combining the evidence concerning an unknown, contained in each of $k$ Bayesian inference bases, is discussed. This can be considered as a generalization of the problem of pooling $k$ priors to determine a consensus prior.…

Statistics Theory · Mathematics 2022-02-08 Michael Evans , Yang Jian Guo

Analogy has received attention as a form of inductive reasoning in the empirical sciences. However, its role in pure mathematics has received less consideration. This paper provides an account of how an analogy with a more familiar…

History and Overview · Mathematics 2022-06-16 Francesco Nappo , Nicolò Cangiotti , Caterina Sisti

In earlier work, we introduced flexible inference and decision-theoretic metareasoning to address the intractability of normative inference. Here, rather than pursuing the task of computing beliefs and actions with decision models composed…

Artificial Intelligence · Computer Science 2013-02-21 Eric J. Horvitz , Adrian Klein

The usual reading of logical implication "A implies B" as "if A then B" fails in intuitionistic logic: there are formulas A and B such that "A implies B" is not provable, even though B is provable whenever A is provable. Intuitionistic…

Logic in Computer Science · Computer Science 2018-10-18 Andrea Condoluci , Matteo Manighetti

Recent authors have proposed analyzing conditional reasoning through a notion of intervention on a simulation program, and have found a sound and complete axiomatization of the logic of conditionals in this setting. Here we extend this…

Artificial Intelligence · Computer Science 2018-07-31 Duligur Ibeling

This paper proposes a careful separation between an entity's epistemic system and their decision system. Crucially, Bayesian counterfactuals are estimated by the epistemic system; not by the decision system. Based on this remark, I prove…

Theoretical Economics · Economics 2020-08-11 Lê Nguyên Hoang

The classical conception of falsification presents scientific theories as entities that are decisively refuted when their predictions fail. This picture has long been challenged by both philosophical analysis and scientific practice, yet…

Other Statistics · Statistics 2025-12-09 Tommaso Costa

We develop a model of abduction in abstract argumentation, where changes to an argumentation framework act as hypotheses to explain the support of an observation. We present dialogical proof theories for the main decision problems (i.e.,…

Artificial Intelligence · Computer Science 2014-07-16 Richard Booth , Dov Gabbay , Souhila Kaci , Tjitze Rienstra , Leendert van der Torre

Probability theory as extended logic is completed such that essentially any probability may be determined. This is done by considering propositional logic (as opposed to predicate logic) as syntactically suffcient and imposing a symmetry…

Statistics Theory · Mathematics 2014-08-12 Cael L. Hasse

When eliciting opinions from a group of experts, traditional devices used to promote honest reporting assume that there is an observable future outcome. In practice, however, this assumption is not always reasonable. In this paper, we…

Multiagent Systems · Computer Science 2013-10-23 Arthur Carvalho , Stanko Dimitrov , Kate Larson
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