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Bayesian probability theory is one of the most successful frameworks to model reasoning under uncertainty. Its defining property is the interpretation of probabilities as degrees of belief in propositions about the state of the world…

Artificial Intelligence · Computer Science 2015-04-27 Pedro A. Ortega

We study implicational formulas in the context of proof complexity of intuitionistic propositional logic (IPC). On the one hand, we give an efficient transformation of tautologies to implicational tautologies that preserves the lengths of…

Logic in Computer Science · Computer Science 2016-10-27 Emil Jeřábek

We present a bounded modified realisability and a bounded functional interpretation of intuitionistic nonstandard arithmetic with nonstandard principles. The functional interpretation is the intuitionistic counterpart of Ferreira and…

Logic · Mathematics 2017-12-14 Bruno Dinis , Jaime Gaspar

Bayesian inference is a popular approach to calibrating uncertainties, but it can underpredict such uncertainties when model misspecification is present, impacting its reliability to inform decision making. Recently, the statistics and…

Computational Engineering, Finance, and Science · Computer Science 2026-01-09 Rebekah White , Rileigh Bandy , Teresa Portone

When dealing with Bayesian inference the choice of the prior often remains a debatable question. Empirical Bayes methods offer a data-driven solution to this problem by estimating the prior itself from an ensemble of data. In the…

Methodology · Statistics 2020-05-13 Ilja Klebanov , Alexander Sikorski , Christof Schütte , Susanna Röblitz

It is standard to regard the intuitionistic restriction of a classical logic as increasing the expressivity of the logic because the classical logic can be adequately represented in the intuitionistic logic by double-negation, while the…

Logic in Computer Science · Computer Science 2010-06-17 Kaustuv Chaudhuri

A common concern with Bayesian methodology in scientific contexts is that inferences can be heavily influenced by subjective biases. As presented here, there are two types of bias for some quantity of interest: bias against and bias in…

Statistics Theory · Mathematics 2019-03-06 Michael Evans , Yang Guo

We revisit and generalize the concept of composite likelihood as a method to make a probabilistic inference by aggregation of multiple Bayesian agents, thereby defining a class of predictive models which we call composite Bayesian. This…

Computation · Statistics 2019-04-18 Alexis Roche

Several recent results bring into focus the superintuitionistic nature of most notions of proof-theoretic validity, but little work has been done evaluating the consequences of these results. Proof-theoretic validity claims to offer a…

Logic · Mathematics 2023-05-17 Will Stafford

Intuitionistic epistemic logic introduces an epistemic operator, which reflects the intended BHK semantics of intuitionism, to intuitionistic logic. The fundamental assumption concerning intuitionistic knowledge and belief is that it is the…

Logic · Mathematics 2016-01-14 Tudor Protopopescu

C. I. Lewis invented modern modal logic as a theory of "strict implication". Over the classical propositional calculus one can as well work with the unary box connective. Intuitionistically, however, the strict implication has greater…

Logic in Computer Science · Computer Science 2017-10-31 Tadeusz Litak , Albert Visser

An agent often has a number of hypotheses, and must choose among them based on observations, or outcomes of experiments. Each of these observations can be viewed as providing evidence for or against various hypotheses. All the attempts to…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

Specifying a Bayesian prior is notoriously difficult for complex models such as neural networks. Reasoning about parameters is made challenging by the high-dimensionality and over-parameterization of the space. Priors that seem benign and…

Machine Learning · Statistics 2020-10-22 Eric Nalisnick , Jonathan Gordon , José Miguel Hernández-Lobato

This paper relates comparative belief structures and a general view of belief management in the setting of deductively closed logical representations of accepted beliefs. We show that the range of compatibility between the classical…

Artificial Intelligence · Computer Science 2013-02-01 Didier Dubois , Helene Fargier , Henri Prade

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

A standard form of analysis for linguistic typology is the universal implication. These implications state facts about the range of extant languages, such as ``if objects come after verbs, then adjectives come after nouns.'' Such…

Computation and Language · Computer Science 2009-07-07 Hal Daumé , Lyle Campbell

The generality of a derivation is an equivalence relation on the set of occurrences of variables in its premises and conclusion such that two occurrences of the same variable are in this relation iff they must remain occurrences of the same…

Logic · Mathematics 2016-04-11 K. Dosen , Z. Petric

We extend the meet-implication fragment of propositional intuitionistic logic with a meet-preserving modality. We give semantics based on semilattices and a duality result with a suitable notion of descriptive frame. As a consequence we…

Logic · Mathematics 2023-06-22 Jim de Groot , Dirk Pattinson

A paraconsistent type theory (an extension of a fragment of intuitionistic type theory by adding opposite types) is here extended by adding co-function types. It is shown that, in the extended paraconsistent type system, the opposite type…

Logic in Computer Science · Computer Science 2022-04-11 Juan C. Agudelo-Agudelo , Andrés Sicard-Ramírez

Spurious ambiguity is the phenomenon whereby distinct derivations in grammar may assign the same structural reading, resulting in redundancy in the parse search space and inefficiency in parsing. Understanding the problem depends on…

Logic in Computer Science · Computer Science 2015-11-16 Glyn Morrill , Oriol Valentín