Results 11 to 20 of about 90,486 (306)
Nonmonotonic Probabilistic Logics between Model-Theoretic Probabilistic Logic and Probabilistic Logic under Coherence [PDF]
arXiv, 2002 Recently, it has been shown that probabilistic entailment under coherence is weaker than model-theoretic probabilistic entailment. Moreover, probabilistic entailment under coherence is a generalization of default entailment in System P. In this paper, we continue this line of research by presenting probabilistic generalizations of more sophisticated ...
arxiv +3 more sources
A Modal Characterization Theorem for a Probabilistic Fuzzy Description Logic [PDF]
arXiv, 2019 The fuzzy modality `probably` is interpreted over probabilistic type spaces by taking expected truth values. The arising probabilistic fuzzy description logic is invariant under probabilistic bisimilarity; more informatively, it is non-expansive wrt. a suitable notion of behavioural distance.
P. Wild +3 more
arxiv +3 more sources
Probability Logic and Probabilistic Induction
Epidemiology, 1998 This article reviews some philosophical aspects of probability and describes how probability logic can give precise meanings to the concepts of inductive support, corroboration, refutation, and related notions, as well as provide a foundation for logically sound statistical inference.
Sander Greenland
openalex +4 more sources
A programmable hybrid digital chemical information processor based on the Belousov-Zhabotinsky reaction. [PDF]
Nat CommunThe exponential growth of the power of modern digital computers is based upon the miniaturization of vast nanoscale arrays of electronic switches, but this will be eventually constrained by fabrication limits and power dissipation.
Sharma A +4 more
europepmc +2 more sources
Probabilistic Similarity Logic
, 2012 Many machine learning applications require the ability to learn from and reason about noisy multi-relational data. To address this, several effective representations have been developed that provide both a language for expressing the structural regularities of a domain, and principled support for probabilistic inference.
Matthias Bröcheler +2 more
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Learning Probabilistic Logic Models from Probabilistic Examples. [PDF]
Mach Learn, 2008 Chen J, Muggleton S, Santos J.
europepmc +3 more sources
Coalgebraic Semantics for Probabilistic Logic Programming [PDF]
Logical Methods in Computer Science, 2021 Probabilistic logic programming is increasingly important in artificial intelligence and related fields as a formalism to reason about uncertainty. It generalises logic programming with the possibility of annotating clauses with probabilities. This paper
Tao Gu, Fabio Zanasi
doaj +1 more source
New Developments in Chinese Studies of Contemporary Inductive Logic
Asian Studies, 2022 Contemporary Chinese studies in inductive logic have long revolved around the unfolding of a philosophical investigation into Hume’s problem. Led by research in probabilistic logic, the principal content of contemporary Chinese logic consists of ...
Xiaoming Ren
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A Probabilistic Higher-order Fixpoint Logic [PDF]
Logical Methods in Computer Science, 2021 We introduce PHFL, a probabilistic extension of higher-order fixpoint logic, which can also be regarded as a higher-order extension of probabilistic temporal logics such as PCTL and the $\mu^p$-calculus. We show that PHFL is strictly more expressive than
Yo Mitani +2 more
doaj +1 more source
Optimizing Probabilities in Probabilistic Logic Programs [PDF]
Theory and Practice of Logic Programming 21 (2021) 543-556, 2021 Probabilistic Logic Programming is an effective formalism for encoding problems characterized by uncertainty. Some of these problems may require the optimization of probability values subject to constraints among probability distributions of random variables.
arxiv +1 more source