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While probability theory is normally applied to external environments, there has been some recent interest in probabilistic modeling of the outputs of computations that are too expensive to run. Since mathematical logic is a powerful tool…

Artificial Intelligence · Computer Science 2016-10-10 Scott Garrabrant , Benya Fallenstein , Abram Demski , Nate Soares

In this paper, a possibilistic disjunctive logic programming approach for modeling uncertain, incomplete and inconsistent information is defined. This approach introduces the use of possibilistic disjunctive clauses which are able to…

Artificial Intelligence · Computer Science 2015-03-19 Juan Carlos Nieves , Mauricio Osorio , Ulises Cortés

Selecting a coherent sequence or subset of elements is a fundamental problem in structured prediction, arising in tasks such as detection, trajectory forecasting, and representative subset selection. In many such settings, the target is…

Machine Learning · Computer Science 2026-05-12 Noam Mizrachi , Nadav Har-Tuv , Shai Shalev-Shwartz

The paper studies the containment companion of a logic $\vdash$. This consists of the consequence relation $\vdash^{r}$ which satisfies all the inferences of $\vdash$, where the variables of the conclusion are \emph{contained} into those of…

Logic · Mathematics 2020-05-05 Stefano Bonzio , Michele Pra Baldi

The field of statistical relational learning aims at unifying logic and probability to reason and learn from data. Perhaps the most successful paradigm in the field is probabilistic logic programming: the enabling of stochastic primitives…

Machine Learning · Computer Science 2018-09-20 Stefanie Speichert , Vaishak Belle

We propose a novel logic, called Frame Logic (FL), that extends first-order logic (with recursive definitions) using a construct Sp(.) that captures the implicit supports of formulas -- the precise subset of the universe upon which their…

Logic in Computer Science · Computer Science 2022-09-27 Adithya Murali , Lucas Peña , Christof Löding , P. Madhusudan

Large language models (LLMs) have become the norm in natural language processing (NLP), excelling in few-shot in-context learning (ICL) with their remarkable abilities. Nonetheless, the success of ICL largely hinges on the choice of…

Computation and Language · Computer Science 2025-05-06 Xingxuan Li , Xuan-Phi Nguyen , Shafiq Joty , Lidong Bing

We introduce proper display calculi for intuitionistic, bi-intuitionistic and classical linear logics with exponentials, which are sound, complete, conservative, and enjoy cut-elimination and subformula property. Based on the same design,…

Logic · Mathematics 2016-11-15 Giuseppe Greco , Alessandra Palmigiano

This note is concerned with a formal analysis of the problem of non-monotonic reasoning in intelligent systems, especially when the uncertainty is taken into account in a quantitative way. A firm connection between logic and probability is…

Artificial Intelligence · Computer Science 2013-04-05 Hung-Trung Nguyen

Unification of logic variables instantly connects present and future observations of their value, independently of their location in the data areas of the runtime system. The paper extends this property to "interclausal logic variables", an…

Programming Languages · Computer Science 2014-06-06 Paul Tarau , Fahmida Hamid

We introduce a new propositional logic, called very weak subintuitionistic logic $\mathbf{VF}$, by adapting the relational semantics of Fitting, Marek, and Truszczy\'nski for the pure logic of necessitation $\mathbf{N}$ to the propositional…

Logic · Mathematics 2026-05-21 Taishi Kurahashi , Mashu Noguchi

The non-deterministic algorithmic procedure PEARL (an acronym for `Propositional variables Elimination Algorithm for Relevance Logic') has been recently developed for computing first-order equivalents of formulas of the language of…

Logic in Computer Science · Computer Science 2021-08-17 Willem Conradie , Valntin Goranko , Peter Jipsen

Large language models (LLMs) are a promising venue for natural language understanding and generation tasks. However, current LLMs are far from reliable: they are prone to generate non-factual information and, more crucially, to contradict…

Machine Learning · Computer Science 2024-04-22 Diego Calanzone , Stefano Teso , Antonio Vergari

Rule based reasoning (RBR) and case based reasoning (CBR) have emerged as two important and complementary reasoning methodologies in artificial intelligence (Al). For problem solving in complex, real world situations, it is useful to…

Artificial Intelligence · Computer Science 2013-04-05 Soumitra Dutta , Piero P. Bonissone

The first contribution of this paper is the presentation of a Pavelka - like formulation of possibilistic logic in which the language is naturally enriched by two connectives which represent negation (eg) and a new type of conjunction…

Artificial Intelligence · Computer Science 2013-02-21 Luca Boldrin , Claudio Sossai

This work is the first exploration of proof-theoretic semantics for a substructural logic. It focuses on the base-extension semantics (B-eS) for intuitionistic multiplicative linear logic (IMLL). The starting point is a review of…

Logic in Computer Science · Computer Science 2024-11-13 Alexander V. Gheorghiu , Tao Gu , David J. Pym

Based on the ideas of quantum theory of open systems (QTOS) we propose the consistent approach to study probabilistic many-valued propositional logic of intelligent devices that are composed from separate but interconnected logical units.…

Quantum Physics · Physics 2013-01-24 E. D. Vol

We give a comprehensive account on the parameterized complexity of model checking and satisfiability of propositional inclusion and independence logic. We discover that for most parameterizations the problems are either in FPT or…

Logic in Computer Science · Computer Science 2023-07-14 Yasir Mahmood , Jonni Virtema

We present a novel asynchronous hyper linear time temporal logic named LPrL (Linear Time Predicate Logic) and establish its basic theory. LPrL is a natural first order extension of LTL (Linear time temporal logic), in which the predicates…

Logic in Computer Science · Computer Science 2026-01-22 Parasara Sridhar Duggirala , P. S. Thiagarajan

Polynomial closure is a standard operator which is applied to a class of regular languages. In the paper, we investigate three restrictions called left (LPol), right (RPol) and mixed polynomial closure (MPol). The first two were known while…

Formal Languages and Automata Theory · Computer Science 2023-01-03 Thomas Place