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In the same sense as classical logic is a formal theory of truth, the recently initiated approach called computability logic is a formal theory of computability. It understands (interactive) computational problems as games played by a…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

In this paper we prove that all the existing conditional event algebras embed into a three-valued extension of temporal logic of discrete past time, which the authors of this paper have proposed in anothe paper as a general model of…

Artificial Intelligence · Computer Science 2007-05-23 Jerzy Tyszkiewicz , Achim Hoffmann , Arthur Ramer

In an earlier paper, a new theory of measurefree "conditional" objects was presented. In this paper, emphasis is placed upon the motivation of the theory. The central part of this motivation is established through an example involving a…

Artificial Intelligence · Computer Science 2013-04-11 I. R. Goodman

Sequent-type proof systems constitute an important and widely-used class of calculi well-suited for analysing proof search. In my master's thesis, I introduce sequent-type calculi for a variant of default logic employing \Lukasiewicz's…

Logic in Computer Science · Computer Science 2019-05-14 Sopo Pkhakadze

We present a computable algorithm that assigns probabilities to every logical statement in a given formal language, and refines those probabilities over time. For instance, if the language is Peano arithmetic, it assigns probabilities to…

Artificial Intelligence · Computer Science 2020-12-09 Scott Garrabrant , Tsvi Benson-Tilsen , Andrew Critch , Nate Soares , Jessica Taylor

We introduce a generalized logic programming paradigm where programs, consisting of facts and rules with the usual syntax, can be enriched by co-facts, which syntactically resemble facts but have a special meaning. As in coinductive logic…

Programming Languages · Computer Science 2017-09-26 Davide Ancona , Francesco Dagnino , Elena Zucca

In this paper we present a propositional logic programming language for reasoning under possibilistic uncertainty and representing vague knowledge. Formulas are represented by pairs (A, c), where A is a many-valued proposition and c is…

Artificial Intelligence · Computer Science 2013-01-18 Teresa Alsinet , Lluis Godo

Language models are increasingly being used in important decision pipelines, so ensuring the correctness of their outputs is crucial. Recent work has proposed evaluating the "factuality" of claims decomposed from a language model generation…

Computation and Language · Computer Science 2025-05-26 Maxon Rubin-Toles , Maya Gambhir , Keshav Ramji , Aaron Roth , Surbhi Goel

We develop a classical propositional logic for reasoning about combinatory logic. We define its syntax, axiomatic system and semantics. The syntax and axiomatic system are presented based on classical propositional logic, with typed…

Logic · Mathematics 2022-12-14 Simona Kašterović , Silvia Ghilezan

We introduce a formal logical language, called conditional probability logic (CPL), which extends first-order logic and which can express probabilities, conditional probabilities and which can compare conditional probabilities. Intuitively…

Logic · Mathematics 2021-08-19 Vera Koponen

We propose a combination of probabilistic reasoning from conditional constraints with approaches to default reasoning from conditional knowledge bases. In detail, we generalize the notions of Pearl's entailment in system Z, Lehmann's…

Artificial Intelligence · Computer Science 2007-05-23 Thomas Lukasiewicz

Abductive forgetting is removing variables from a logical formula while maintaining its abductive explanations. It is carried in two alternative ways depending on its intended application. Both differ from the usual forgetting, which…

Logic in Computer Science · Computer Science 2025-07-22 Paolo Liberatore

Entities and events are crucial to natural language reasoning and common in procedural texts. Existing work has focused either exclusively on entity state tracking (e.g., whether a pan is hot) or on event reasoning (e.g., whether one would…

Computation and Language · Computer Science 2023-02-17 Li Zhang , Hainiu Xu , Yue Yang , Shuyan Zhou , Weiqiu You , Manni Arora , Chris Callison-Burch

A semantics is given to possibilistic logic, a logic that handles weighted classical logic formulae, and where weights are interpreted as lower bounds on degrees of certainty or possibility, in the sense of Zadeh's possibility theory. The…

Artificial Intelligence · Computer Science 2013-03-26 Jerome Lang , Didier Dubois , Henri Prade

Two major difficulties in using default logics are their intractability and the problem of selecting among multiple extensions. We propose an approach to these problems based on integrating nommonotonic reasoning with plausible reasoning…

Artificial Intelligence · Computer Science 2013-04-08 Piero P. Bonissone , David A. Cyrluk , James W. Goodwin , Jonathan Stillman

This paper studies axioms for nonmonotonic consequences from a semantics-based point of view, focusing on a class of mathematical structures for reasoning about partial information without a predefined syntax/logic. This structure is called…

Logic in Computer Science · Computer Science 2007-05-23 Guo-Qiang Zhang

The semantics for counterfactuals due to David Lewis has been challenged on the basis of unlikely, or impossible, events. Such events may skew a given similarity order in favour of those possible worlds which exhibit them. By updating the…

Logic in Computer Science · Computer Science 2016-06-28 Patrick Girard , Marcus Anthony Triplett

We present a coherence-based probability semantics and probability propagation rules for (categorical) Aristotelian syllogisms. For framing the Aristotelian syllogisms as probabilistic inferences, we interpret basic syllogistic sentence…

Probability · Mathematics 2023-04-04 Niki Pfeifer , Giuseppe Sanfilippo

The unification of logic and probability is a long-standing concern in AI, and more generally, in the philosophy of science. In essence, logic provides an easy way to specify properties that must hold in every possible world, and…

Artificial Intelligence · Computer Science 2020-06-18 Vaishak Belle

Conditional probabilities are a core concept in machine learning. For example, optimal prediction of a label $Y$ given an input $X$ corresponds to maximizing the conditional probability of $Y$ given $X$. A common approach to inference tasks…

Machine Learning · Computer Science 2017-08-09 Yoav Wald , Amir Globerson