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Related papers: Restricted Rules of Inference and Paraconsistency

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Possibilistic logic is a well-known graded logic of uncertainty suitable to reason under incomplete information and partially inconsistent knowledge, which is built upon classical first order logic. There exists for Possibilistic logic a…

Artificial Intelligence · Computer Science 2013-01-31 Teresa Alsinet , Lluis Godo , Sandra Sandri

In this article, the hierarchy of LFIs L$_n^k$, Logics of Controlled Consistency (LCC), is introduced. Inspired by da Costa's original C$_n$ systems, this hierarchy can represent different degrees of paraconsistent commitment and different…

Logic in Computer Science · Computer Science 2026-04-22 Marcelo E. Coniglio , Rafael Ongaratto

Large language models achieve strong reasoning performance, but inference strategies such as Self-Consistency (SC) are computationally expensive, as they fully expand all reasoning traces. We introduce PoLR (Path of Least Resistance), the…

Artificial Intelligence · Computer Science 2026-02-04 Ishan Jindal , Sai Prashanth Akuthota , Jayant Taneja , Sachin Dev Sharma

Distributive laws are important for algebraic reasoning in arithmetic and logic. They are equally important for algebraic reasoning about concurrent programs. In existing theories such as Concurrent Kleene Algebra, only partial correctness…

Logic in Computer Science · Computer Science 2024-03-21 Larissa A. Meinicke , Ian J. Hayes

Many commonsense reasoning NLP tasks involve choosing between one or more possible answers to a question or prompt based on knowledge that is often implicit. Large pretrained language models (PLMs) can achieve near-human performance on such…

Computation and Language · Computer Science 2021-06-15 Bhargavi Paranjape , Julian Michael , Marjan Ghazvininejad , Luke Zettlemoyer , Hannaneh Hajishirzi

We will investigate proof-theoretic and linguistic aspects of first-order linear logic. We will show that adding partial order constraints in such a way that each sequent defines a unique linear order on the antecedent formulas of a sequent…

Logic in Computer Science · Computer Science 2020-08-17 Richard Moot

The purpose of this paper is to introduce justification logics based on conditional logics. We introduce a new family of logics, called conditional justification logics, which incorporates a counterfactual conditional in its language. For…

Logic · Mathematics 2025-01-17 Meghdad Ghari

Intuitionistic logic extended with decidable propositional atoms combines classical properties in its propositional part and intuitionistic properties for derivable formulas not containing propositional symbols. Sequent calculus is used as…

General Mathematics · Mathematics 2007-05-23 Alexander Sakharov

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

We address the problem of structural disambiguation in syntactic parsing. In psycholinguistics, a number of principles of disambiguation have been proposed, notably the Lexical Preference Rule (LPR), the Right Association Principle (RAP),…

cmp-lg · Computer Science 2008-02-03 Hang Li

In this paper, we develop a novel verification technique to reason about programs featuring concurrency, pointers and randomization. While the integration of concurrency and pointers is well studied, little is known about the combination of…

Logic in Computer Science · Computer Science 2024-10-01 Ira Fesefeldt , Joost-Pieter Katoen , Thomas Noll

The widespread application of pre-trained language models (PLMs) in natural language processing (NLP) has led to increasing concerns about their explainability. Selective rationalization is a self-explanatory framework that selects…

Computation and Language · Computer Science 2025-01-07 Libing Yuan , Shuaibo Hu , Kui Yu , Le Wu

In-context reinforcement learning (ICRL) leverages the in-context learning capabilities of transformer models (TMs) to efficiently generalize to unseen sequential decision-making tasks without parameter updates. However, existing ICRL…

Machine Learning · Computer Science 2026-02-10 Juncheng Dong , Bowen He , Moyang Guo , Ethan X. Fang , Zhuoran Yang , Vahid Tarokh

We introduce some classical complexity-theoretic techniques to Parameterized Complexity. First, we study relativization for the machine models that were used by Chen, Flum, and Grohe (2005) to characterize a number of parameterized…

Computational Complexity · Computer Science 2018-07-18 Ralph Christian Bottesch

We develop a method to recognize admissibility of $\Pi_{2}$-rules, relating this problem to a specific instance of the unification problem with linear constants restriction, called here "unification with simple variable restriction". It is…

Logic · Mathematics 2024-06-06 Rodrigo Nicolau Almeida , Silvio Ghilardi

In this paper, we propose a new logic for expressing and reasoning about probabilistic hyperproperties. Hyperproperties characterize the relation between different independent executions of a system. Probabilistic hyperproperties express…

Logic in Computer Science · Computer Science 2018-04-06 Erika Abraham , Borzoo Bonakdarpour

This paper concerns an expansion of first-order Belnap-Dunn logic whose connectives and quantifiers all have a counterpart in classical logic. The language and logical consequence relation of this paradefinite logic are defined, a sequent…

Logic in Computer Science · Computer Science 2026-03-04 C. A. Middelburg

LLM-based explainable recommenders can produce fluent explanations that are factually correct, yet still justify items using attributes that conflict with a user's historical preferences. Such preference-inconsistent explanations yield…

Artificial Intelligence · Computer Science 2026-05-08 Chengkai Wang , Baisong Liu

We introduce two-dimensional logics based on \L{}ukasiewicz and G\"{o}del logics to formalize paraconsistent fuzzy reasoning. The logics are interpreted on matrices, where the common underlying structure is the bi-lattice (twisted) product…

Logic · Mathematics 2022-05-31 Marta Bílková , Sabine Frittella , Daniil Kozhemiachenko

Mathematical reasoning flexibility across physics contexts is a desirable learning outcome of introductory physics, where the math world and physical world meet. Physics Quantitative Literacy (PQL) is a set of interconnected skills and…

Physics Education · Physics 2019-11-06 Suzanne White Brahmia , Alexis Olsho , Andrew Boudreaux , Trevor Smith , Charlotte Zimmerman